# Best Analytics Platforms - Page 2

## How Many Analytics Platforms Products Does G2 Track?

**Total Products under this Category:** 366

### Category Stats (Jul 2026)

- **Average Rating:** 4.5/5 (↑0.01 vs Jun 2026) The average rating of products in this category, based on all submitted ratings
- **Top Trending Product:** Aible (+4.36%) - Among all products in this category, Aible recorded the largest rating increase compared to last month

_Last updated: July 31, 2026_

## How Does G2 Rank Analytics Platforms Products?

**Why You Can Trust G2's Software Rankings:**

- 30 Analysts and Data Experts
- 28,800+ Authentic Reviews
- 366+ Products
- Unbiased Rankings

G2's software rankings are built on verified user reviews, rigorous moderation, and a consistent research methodology maintained by a team of analysts and data experts. Each product is measured using the same transparent criteria, with no paid placement or vendor influence. While reviews reflect real user experiences, which can be subjective, they offer valuable insight into how software performs in the hands of professionals. Together, these inputs power the G2 Score, a standardized way to compare tools within every category.

## G2 Grid® for Analytics Platforms
 ![G2 Grid® for Analytics Platforms plotting products by satisfaction and market presence](https://www.g2.com/categories/analytics-platforms/grids.png?focus%5B%5D=29364&focus%5B%5D=1213&focus%5B%5D=10470&focus%5B%5D=1327283&focus%5B%5D=989&focus%5B%5D=604&focus%5B%5D=5048&focus%5B%5D=27024)

Highlighted products: Microsoft Power BI, Tableau, Databricks, SAS Viya, Alteryx, Domo, Looker, and Kyvos Semantic Layer.

Underlying data: [Grid® JSON](https://www.g2.com/categories/analytics-platforms/grids.json?focus%5B%5D=microsoft-microsoft-power-bi&focus%5B%5D=tableau&focus%5B%5D=databricks&focus%5B%5D=sas-sas-viya&focus%5B%5D=alteryx&focus%5B%5D=domo&focus%5B%5D=looker&focus%5B%5D=kyvos-semantic-layer&segment=all)

**Sponsored**

### KNIME

KNIME helps everybody make sense of data. Its free and open source KNIME Analytics Platform enables anyone — whether they come from a business, technical or data background — to intuitively work with data, every day. KNIME Business Hub is the commercial complement to KNIME Analytics Platform and enables users to collaborate on data science and share insights across the organization. Together, the products support the complete data science lifecycle, allowing teams at all levels of analytics readiness to support the operationalization of data and to build a scalable data science practice.

[Visit website](https://www.g2.com/external_clickthroughs/record?secure%5Bad_program%5D=ppc&secure%5Bad_slot%5D=category_product_list_llm&secure%5Bcategory_id%5D=620&secure%5Bchosen_at%5D=2026-07-31T20%3A46%3A27Z&secure%5Bdisplayable_resource_id%5D=620&secure%5Bdisplayable_resource_type%5D=Category&secure%5Bmedium%5D=sponsored&secure%5Bplacement_reason%5D=page_category&secure%5Bplacement_resource_ids%5D%5B%5D=620&secure%5Bprioritized%5D=false&secure%5Bproduct_id%5D=16291&secure%5Bresource_id%5D=620&secure%5Bresource_type%5D=Category&secure%5Bsource_type%5D=category_page&secure%5Bsource_url%5D=https%3A%2F%2Fwww.g2.com%2Fcategories%2Fanalytics-platforms%3Fattributes%255B110%255D%3Dall%26page%3D2%26segment%3Dall%26selected_view%3Dgrid&secure%5Btoken%5D=cbabd88c2a52d418793a2530558e23dd41c62a046d5d92455ababdf034dd9c51&secure%5Burl%5D=https%3A%2F%2Fwww.knime.com%2Flp%2Fdemo%3Futm_medium%3D3rd-party%26utm_source%3DG2%26utm_campaign%3Dbrand%26utm_term%3Dpaid%26utm_content%3D&secure%5Burl_type%5D=custom_url)

### [Yellowfin BI](https://www.g2.com/it/products/yellowfin-bi/reviews)

Yellowfin è l'unica suite di analisi che combina con successo dashboard basate su azioni con analisi automatizzata leader nel settore e narrazione dei dati. Fornendo la migliore esperienza analitica, Yellowfin offre ai tuoi utenti modi unici per interagire e agire sui loro dati, e risponde alle esigenze di analisti di dati, utenti aziendali, clienti e sviluppatori che vogliono costruire, distribuire o utilizzare esperienze analitiche straordinarie. Analisi per aziende di software Integra e incorpora analisi con una differenza nella tua app, a modo tuo \* Sostituisci strumenti di reporting legacy o sviluppati internamente \* Incorpora una suite di analisi moderna e self-service \* Offri un'esperienza cliente eccezionale Analisi per imprese Ottieni più valore dai tuoi dati in modi nuovi e innovativi \* Migra dai fogli di calcolo a una piattaforma di analisi moderna \* Sostituisci applicazioni BI legacy \* Incorpora analisi nei flussi di lavoro operativi Costruttori di Applicazioni Analitiche Sfrutta la tua esperienza nel dominio per creare prodotti di dati che deliziano \* Crea applicazioni uniche basate sui dati \* Chiudi il cerchio sull'analisi \* Offri approfondimenti come servizio

**Average Rating:** 4.4/5.0

**Total Reviews:** 419

#### How Do G2 Users Rate Yellowfin BI?

- **Ritiene che the product sia stato un valido partner commerciale?:** 8.9/10 (Category avg: 9.1/10)
- **Passaggi per rispondere:** 8.0/10 (Category avg: 8.4/10)
- **Interfaccia dei Rapporti:** 8.6/10 (Category avg: 8.7/10)
- **Campi Calcolati:** 8.2/10 (Category avg: 8.5/10)

#### Who Is the Company Behind Yellowfin BI?

- **Venditore:** [Yellowfin](https://www.g2.com/it/sellers/yellowfin)
- **Anno di Fondazione:** 2003
- **Sede centrale:** Austin, Texas
- **Twitter:** @YellowfinBI  
5,783 follower su Twitter
- **Pagina LinkedIn®:** [www.linkedin.com](https://www.g2.com/it/external_clickthroughs/record?secure%5Bsource_type%5D=product_profile&secure%5Btoken%5D=33032d8c5dedebf7f5eb6ce16c77c740fc71507c8ac4b965be708a6eced00b34&secure%5Burl%5D=https%3A%2F%2Fwww.linkedin.com%2Fcompany%2F358856%2F&secure%5Burl_type%5D=linkedin_company_website)  
65 dipendenti su LinkedIn®

#### Who Uses This Product?

- **Who Uses This:** General Manager, Business Analyst
- **Top Industries:** Software per computer, Tecnologia dell'informazione e servizi
- **Company Size:** 46% Small, 35% Medium

#### What Do G2 Reviewers Say About Yellowfin BI?

_AI-generated summary from verified user reviews_

##### Pros

- Gli utenti apprezzano l' **interfaccia intuitiva** di Yellowfin BI, che consente la facile creazione di report e dashboard per tutti i livelli di competenza.
- Gli utenti elogiano Yellowfin BI per la sua **visualizzazione dei dati intuitiva** , che consente una reportistica senza sforzo e una collaborazione efficace.
- Gli utenti apprezzano la **configurazione intuitiva** di Yellowfin BI, che consente un accesso rapido e facile a potenti approfondimenti sui dati.
- Gli utenti apprezzano l' **interfaccia intuitiva** di Yellowfin BI, che consente analisi rapide e collaborative senza ostacoli tecnici.
- Gli utenti apprezzano la **facile personalizzazione del cruscotto** di Yellowfin BI, che consente configurazioni rapide e narrazione efficace dei dati.

##### Cons

- Gli utenti sperimentano una **curva di apprendimento** impegnativa con Yellowfin BI, trovando le funzionalità avanzate non intuitive e la configurazione complessa.
- Gli utenti notano che la **gestione di grandi quantità di dati** può portare a prestazioni più lente e tempi di aggiornamento dei filtri più lunghi.
- Gli utenti notano che le **prestazioni lente** con grandi set di dati limitano l'efficienza, influenzando la loro esperienza complessiva con Yellowfin BI.
- Gli utenti riscontrano **problemi di prestazioni** con tempi di caricamento del cruscotto lenti e aggiornamenti complessi, influenzando l'efficienza complessiva.
- Gli utenti trovano **personalizzazione limitata** in Yellowfin BI, limitando le opzioni di analisi avanzata e design visivo moderno.

#### What Are Recent G2 Reviews of Yellowfin BI?

**["Brillante narrazione dei dati e dashboard robuste con Yellowfin BI"](https://www.g2.com/it/survey_responses/yellowfin-bi-review-12827644)**

**Rating:** 4.5/5.0 stars

_— Luciana S._

[Read full review](https://www.g2.com/it/survey_responses/yellowfin-bi-review-12827644)

**["Yellowfin BI eccelle nel raccontare storie con i dati, nella collaborazione e negli approfondimenti assistiti dall'IA."](https://www.g2.com/it/survey_responses/yellowfin-bi-review-12809222)**

**Rating:** 4.5/5.0 stars

_— Rinalon E._

[Read full review](https://www.g2.com/it/survey_responses/yellowfin-bi-review-12809222)

#### What Are G2 Users Discussing About Yellowfin BI?

- [A cosa serve Yellowfin BI?](https://www.g2.com/it/discussions/what-is-yellowfin-bi-used-for)
- [What should I look for in a BI tool?](https://www.g2.com/it/discussions/what-should-i-look-for-in-a-bi-tool)
- [Qual è il miglior software di BI?](https://www.g2.com/it/discussions/what-is-the-best-bi-software) - 1 comment
- [What are the benefits of business intelligence?](https://www.g2.com/it/discussions/what-are-the-benefits-of-business-intelligence)
- [What are the features of Business Intelligence?](https://www.g2.com/it/discussions/what-are-the-features-of-business-intelligence)

### [FICO Analytics Workbench™](https://www.g2.com/products/fico-analytics-workbencha/reviews)

FICO® Analytics Workbench™ is a comprehensive predictive analytics tool designed to empower businesses in developing and deploying explainable machine learning models. It caters to both business users and data scientists, facilitating data exploration, visual data wrangling, decision strategy design, and machine learning within a unified environment. The platform is built on the high-performance FICO® Decision Management Platform, ensuring scalability and integration with real-time business operations. Key Features and Functionality: - Explainable AI Toolkit: Provides transparency in AI-derived decisions, enabling users to validate and interpret machine learning models effectively. - Integrated Development Environment: Combines decision trees, scorecards, and machine learning techniques, offering a versatile toolkit for model development. - User-Friendly Interface: Designed for users with varying skill sets, from business analysts to data scientists, promoting collaboration and productivity. - Cloud-Based Deployment: Offers a cloud-ready solution, allowing for scalable and flexible deployment options. - Regulatory Compliance Support: Automates the production of necessary documentation to meet internal review and external regulatory requirements. Primary Value and Problem Solving: FICO® Analytics Workbench™ addresses the growing need for transparent and interpretable AI models in business decision-making. By providing tools that make machine learning models explainable, it helps organizations comply with regulatory standards and build trust in AI-driven decisions. The platform's intuitive design and comprehensive features enable faster time-to-value, enhanced productivity, and improved business outcomes through analytically powered decisions.

**Average Rating:** 4.3/5.0

**Total Reviews:** 11

#### How Do G2 Users Rate FICO Analytics Workbench™?

- **Has the product been a good partner in doing business?:** 8.7/10 (Category avg: 9.1/10)
- **Steps to Answer:** 8.8/10 (Category avg: 8.4/10)
- **Reports Interface:** 8.8/10 (Category avg: 8.7/10)
- **Calculated Fields:** 9.2/10 (Category avg: 8.5/10)

#### Who Is the Company Behind FICO Analytics Workbench™?

- **Seller:** [FICO](https://www.g2.com/sellers/fico)
- **Year Founded:** 1956
- **HQ Location:** Bozeman, Montana
- **LinkedIn® Page:** [www.linkedin.com](https://www.g2.com/external_clickthroughs/record?secure%5Bsource_type%5D=product_profile&secure%5Btoken%5D=2314f7c9d8f522450d313bcbc9f5016b1c07ffcc0b86a4643948f011da1081dc&secure%5Burl%5D=https%3A%2F%2Fwww.linkedin.com%2Fcompany%2Ffico%2F&secure%5Burl_type%5D=linkedin_company_website)  
3,806 employees on LinkedIn®
- **Ownership:** NYSE:FICO
- **Total Revenue (USD mm):** $1,294

#### Who Uses This Product?

- **Company Size:** 45% Large, 27% Medium

#### What Do G2 Reviewers Say About FICO Analytics Workbench™?

_AI-generated summary from verified user reviews_

##### Pros

- Users value the **ease of use** of FICO Analytics Workbench™, enhancing their overall efficiency and experience.

#### What Are Recent G2 Reviews of FICO Analytics Workbench™?

**["From Messy Data to Magic Models: FICO Workbench to the Rescue"](https://www.g2.com/survey_responses/fico-analytics-workbench-review-9701975)**

**Rating:** 4.5/5.0 stars

_— Verified User in Industrial Automation_

[Read full review](https://www.g2.com/survey_responses/fico-analytics-workbench-review-9701975)

**["Fico Analytics Review"](https://www.g2.com/survey_responses/fico-analytics-workbench-review-11044918)**

**Rating:** 5.0/5.0 stars

_— Starr C._

[Read full review](https://www.g2.com/survey_responses/fico-analytics-workbench-review-11044918)

### [Dataiku](https://www.g2.com/products/dataiku/reviews)

Dataiku is the Platform for AI Success: the AI orchestration layer where enterprises build, deploy, and govern analytics, models, and agents at scale. It sits on top of the data platforms, clouds, and AI services you already use, working across all of them without locking you into any one. Dataiku expands who can build production AI, putting the right tools in the hands of data scientists and domain experts alike, from fraud analysts to demand planners. It orchestrates machine learning, rules, LLMs, and agents as one governed system, built on more than a decade of running production AI. Governance is part of the build rather than something bolted on afterward, so teams ship faster while keeping performance, cost, and risk under control. The result: AI that moves from experimentation to trusted, measurable execution now, not in 18 months.

**Average Rating:** 4.4/5.0

**Total Reviews:** 213

#### How Do G2 Users Rate Dataiku?

- **Has the product been a good partner in doing business?:** 8.6/10 (Category avg: 9.1/10)
- **Steps to Answer:** 7.8/10 (Category avg: 8.4/10)
- **Reports Interface:** 7.8/10 (Category avg: 8.7/10)
- **Calculated Fields:** 8.2/10 (Category avg: 8.5/10)

#### Who Is the Company Behind Dataiku?

- **Seller:** [Dataiku](https://www.g2.com/sellers/dataiku)
- **Company Website:** Dataiku.com
- **Year Founded:** 2013
- **HQ Location:** New York, NY
- **Twitter:** @dataiku  
22,917 Twitter followers
- **LinkedIn® Page:** [www.linkedin.com](https://www.g2.com/external_clickthroughs/record?secure%5Bsource_type%5D=product_profile&secure%5Btoken%5D=e59ec8fccc02ecc4f883419e54da56d3f6fc8b1e556153f0cc01cd05e3b77faa&secure%5Burl%5D=https%3A%2F%2Fwww.linkedin.com%2Fcompany%2Fdataiku%2F&secure%5Burl_type%5D=linkedin_company_website)  
1,619 employees on LinkedIn®

#### Who Uses This Product?

- **Who Uses This:** Data Scientist, Data Analyst
- **Top Industries:** Financial Services, Pharmaceuticals
- **Company Size:** 60% Large, 22% Medium

#### What Do G2 Reviewers Say About Dataiku?

_AI-generated summary from verified user reviews_

##### Pros

- Users appreciate how Dataiku facilitates **easy ML development** , allowing focus on building models without the complexity.
- Users love the **ease of use** in Dataiku, simplifying complex tasks and enhancing their data analysis experience.
- Users appreciate the **ease of usability** in Dataiku, enabling collaboration for both technical and non-technical users.
- Users appreciate the **easy integrations** of Dataiku, facilitating smooth collaboration and deployment across various analytics tools.
- Users benefit from the **productivity improvement** of Dataiku, enabling faster project development and enhanced career growth.

##### Cons

- Users find the **steep learning curve** of Dataiku challenging, making it tough for beginners to master the platform.
- Users find the **steep learning curve** challenging for beginners, impacting their ability to effectively use Dataiku.
- Users find the **difficult learning** curve challenging, particularly for beginners navigating advanced features.
- Users experience **slow performance** with Dataiku when handling large datasets, affecting efficiency and productivity.
- Users find Dataiku **expensive** , especially for smaller organizations and projects, impacting accessibility and affordability.

#### What Are Recent G2 Reviews of Dataiku?

**["Unified, Low-Code Platform That Boosts End-to-End Data & AI Productivity"](https://www.g2.com/survey_responses/dataiku-review-13125252)**

**Rating:** 4.5/5.0 stars

_— Ravindra N._

[Read full review](https://www.g2.com/survey_responses/dataiku-review-13125252)

**["Build Faster Workflows with Connected Data from many providers or distinct data sources"](https://www.g2.com/survey_responses/dataiku-review-13120436)**

**Rating:** 4.5/5.0 stars

_— Adalberto G._

[Read full review](https://www.g2.com/survey_responses/dataiku-review-13120436)

#### What Are G2 Users Discussing About Dataiku?

- [Is Dataiku an ETL tool?](https://www.g2.com/discussions/is-dataiku-an-etl-tool)
- [Is Dataiku web based?](https://www.g2.com/discussions/is-dataiku-web-based)
- [What is DSS Dataiku?](https://www.g2.com/discussions/what-is-dss-dataiku)
- [What is Dataiku DSS used for?](https://www.g2.com/discussions/what-is-dataiku-dss-used-for)

### [Count](https://www.g2.com/products/count/reviews)

Count is a modern data collaboration platform that helps data teams actually work together. It combines a data notebook with a real-time collaborative canvas for analysis and visualisation, so everyone can query, debug, and explore data in one place. Count replaces the mess of disconnected tools with a single workspace where analysts, engineers, and stakeholders can write SQL or Python, build visualisations, and share insights instantly. You can import and debug dbt models, see live results from connected CTEs, and export back to dbt Cloud, GitHub, or full SQL scripts. Used by over 500 data teams, including Accenture, Cleo AI, and Too Good To Go, Count helps teams move beyond static dashboards and focus on solving real business problems. It’s data collaboration that actually works.

**Average Rating:** 4.8/5.0

**Total Reviews:** 103

#### How Do G2 Users Rate Count?

- **Has the product been a good partner in doing business?:** 9.5/10 (Category avg: 9.1/10)
- **Steps to Answer:** 8.5/10 (Category avg: 8.4/10)
- **Reports Interface:** 8.5/10 (Category avg: 8.7/10)
- **Calculated Fields:** 8.8/10 (Category avg: 8.5/10)

#### Who Is the Company Behind Count?

- **Seller:** [Count Technologies](https://www.g2.com/sellers/count-technologies)
- **Company Website:** count.co
- **Year Founded:** 2016
- **HQ Location:** London, United Kingdom
- **Twitter:** @counthq  
2,104 Twitter followers
- **LinkedIn® Page:** [www.linkedin.com](https://www.g2.com/external_clickthroughs/record?secure%5Bsource_type%5D=product_profile&secure%5Btoken%5D=0956a6d964e88b30e56b745e48884aede87f2b5b2e3f6bde528e191321aec5b7&secure%5Burl%5D=https%3A%2F%2Fwww.linkedin.com%2Fcompany%2Fcounthq%2F&secure%5Burl_type%5D=linkedin_company_website)  
26 employees on LinkedIn®

#### Who Uses This Product?

- **Who Uses This:** Data Analyst, Analytics Engineer
- **Top Industries:** Financial Services, Information Technology and Services
- **Company Size:** 79% Medium, 11% Large

#### What Do G2 Reviewers Say About Count?

_AI-generated summary from verified user reviews_

##### Pros

- Users value the **collaborative approach** of Count, enhancing teamwork and real-time data sharing effectively.
- Users value the **ease of use** in Count, simplifying data exploration and enhancing collaboration with intuitive tools.
- Users highlight the **responsive customer support** of Count, appreciating quick assistance and a supportive community.
- Users appreciate the **flexibility** of Count, allowing easy data analysis and collaboration for everyone, regardless of technical skills.
- Users praise Count for its **powerful data visualization capabilities** , enhancing exploratory analysis and collaborative reporting effortlessly.

##### Cons

- Users struggle with the **steep learning curve** of Count, especially those unfamiliar with canvas tools like Figma.
- Users experience **slow performance** with large canvases in Count, making navigation and updates frustrating at times.
- Users feel the product has **limited customization options** , hindering their ability to create tailored reports and visuals.
- Users find **missing features** like natural-language queries and basic visuals limit Count's usability and flexibility.
- Users experience **layout issues** that can lead to cluttered canvases, impacting navigation and data exploration workflows.

#### What Are Recent G2 Reviews of Count?

**["Flexible, User-Friendly Collaboration for SQL & Python Analysis with Solid LLM Integration"](https://www.g2.com/survey_responses/count-review-12870160)**

**Rating:** 4.5/5.0 stars

_— Timothy L._

[Read full review](https://www.g2.com/survey_responses/count-review-12870160)

**["Count Streamlines SQL, Python, and Collaborative Data Storytelling"](https://www.g2.com/survey_responses/count-review-13126061)**

**Rating:** 4.5/5.0 stars

_— Ravindra N._

[Read full review](https://www.g2.com/survey_responses/count-review-13126061)

### [Incorta](https://www.g2.com/products/incorta/reviews)

Incorta is the first and only open data delivery platform that enables real-time analysis of live, detailed data across all systems of record—without the need for complex ETL processes. By enabling direct analysis on raw, source-identical data, Incorta provides faster, more accurate insights while removing barriers to exploration. With intuitive low-code/no-code tools, AI-powered querying through Nexus, and prebuilt business data applications, enterprise teams can quickly surface insights, break down technical roadblocks, and make smarter decisions without heavy engineering effort. For more information, please visit www.incorta.com.

**Average Rating:** 4.4/5.0

**Total Reviews:** 55

#### How Do G2 Users Rate Incorta?

- **Has the product been a good partner in doing business?:** 9.4/10 (Category avg: 9.1/10)
- **Steps to Answer:** 9.2/10 (Category avg: 8.4/10)
- **Reports Interface:** 9.3/10 (Category avg: 8.7/10)
- **Calculated Fields:** 9.0/10 (Category avg: 8.5/10)

#### Who Is the Company Behind Incorta?

- **Seller:** [Incorta](https://www.g2.com/sellers/incorta)
- **Company Website:** www.incorta.com
- **Year Founded:** 2013
- **HQ Location:** San Mateo, CA
- **LinkedIn® Page:** [www.linkedin.com](https://www.g2.com/external_clickthroughs/record?secure%5Bsource_type%5D=product_profile&secure%5Btoken%5D=c8c59dc8a9a75b9a6418a91d4025810db481465cf5bce72225b97c66bb082527&secure%5Burl%5D=https%3A%2F%2Fwww.linkedin.com%2Fcompany%2Fincorta%2F&secure%5Burl_type%5D=linkedin_company_website)  
348 employees on LinkedIn®

#### Who Uses This Product?

- **Top Industries:** Information Technology and Services, Computer Software
- **Company Size:** 56% Large, 29% Medium

#### What Do G2 Reviewers Say About Incorta?

_AI-generated summary from verified user reviews_

##### Pros

- Users value the **ease of integration** with diverse data sources and types in Incorta, streamlining their data management.
- Users value the **easy integrations** with various data sources, enhancing their data management experience significantly.
- Users value the **ease of integration** with various data sources and types in Incorta.

##### Cons

- Users face issues with **bugs** as the local data agent may not support the latest JRE builds effectively.

#### What Are Recent G2 Reviews of Incorta?

**["Great platformand support"](https://www.g2.com/survey_responses/incorta-review-10853785)**

**Rating:** 5.0/5.0 stars

_— Jeff W._

[Read full review](https://www.g2.com/survey_responses/incorta-review-10853785)

**["Facilitating presentation and information access"](https://www.g2.com/survey_responses/incorta-review-9467627)**

**Rating:** 5.0/5.0 stars

_— Elsayed H._

[Read full review](https://www.g2.com/survey_responses/incorta-review-9467627)

#### What Are G2 Users Discussing About Incorta?

- [Is Incorta a data warehouse?](https://www.g2.com/discussions/is-incorta-a-data-warehouse)
- [What is Incorta?](https://www.g2.com/discussions/what-is-incorta)
- [What do you know about Incorta?](https://www.g2.com/discussions/what-do-you-know-about-incorta)
- [What is Incorta used for?](https://www.g2.com/discussions/what-is-incorta-used-for) - 1 comment

### [Deepnote](https://www.g2.com/it/products/deepnote/reviews)

Deepnote è uno spazio di lavoro per i dati dove agenti e umani lavorano insieme. È progettato per semplificare l'esplorazione dei dati, accelerare l'analisi e fornire rapidamente intuizioni azionabili per te e il tuo team. A differenza degli strumenti obsoleti come Jupyter, Deepnote è costruito pensando al prossimo decennio. Deepnote dà a chiunque lavori con i dati dei superpoteri. Unifica il tuo flusso di lavoro dei dati attraverso uno strato semantico integrato, preparando i tuoi dati per applicazioni AI avanzate. Puoi anche sfruttare il nostro copilota AI per i dati per chattare con i tuoi dati, creare grafici, scrivere codice o trasformare i tuoi notebook AI in dashboard o app di dati completamente sviluppate. Combina dati, codice SQL o Python e visualizzazioni fianco a fianco su una tela flessibile - migliorata con modelli di ragionamento AI all'avanguardia. 🤖 Analizza con AI • Genera codice e visualizzazioni descrivendo il tuo obiettivo. • Scrivi automaticamente, esegui e correggi il codice con l'AI. • Muoviti più velocemente con suggerimenti AI contestuali. 🔗 Unifica • Connettiti a oltre 60 fonti di dati come BigQuery, Snowflake e PostgreSQL. • Combina Python e SQL in un unico notebook. • Costruisci moduli ETL, analitici e metrici riutilizzabili. • Crea uno strato semantico con definizioni condivise e metriche affidabili. ⚖️ Scala • Aumenta istantaneamente la potenza di calcolo, più inclusa rispetto a Colab. • Pianifica lavori e ricevi notifiche con risultati aggiornati. • Organizza il lavoro in progetti e cartelle per la chiarezza del team. • Gestisci i flussi di lavoro tramite REST API. 🚀 Lancia • Trasforma i notebook in dashboard o app di dati, nativamente o con Streamlit. • Lascia che gli utenti esplorino i dati con input interattivi. • Condividi app sicure e live con un solo clic.

**Average Rating:** 4.5/5.0

**Total Reviews:** 381

#### How Do G2 Users Rate Deepnote?

- **Ritiene che the product sia stato un valido partner commerciale?:** 8.6/10 (Category avg: 9.1/10)
- **Passaggi per rispondere:** 7.7/10 (Category avg: 8.4/10)
- **Interfaccia dei Rapporti:** 8.0/10 (Category avg: 8.7/10)
- **Campi Calcolati:** 8.2/10 (Category avg: 8.5/10)

#### Who Is the Company Behind Deepnote?

- **Venditore:** [Deepnote](https://www.g2.com/it/sellers/deepnote)
- **Sito web dell'azienda:** www.deepnote.com
- **Anno di Fondazione:** 2019
- **Sede centrale:** San Francisco , US
- **Twitter:** @DeepnoteHQ  
5,239 follower su Twitter
- **Pagina LinkedIn®:** [www.linkedin.com](https://www.g2.com/it/external_clickthroughs/record?secure%5Bsource_type%5D=product_profile&secure%5Btoken%5D=0d297cbb8d96f5409e14da076c1669be4aa5b9bc29dd1db4c4a0ea90b79466ed&secure%5Burl%5D=https%3A%2F%2Fwww.linkedin.com%2Fcompany%2Fdeepnote&secure%5Burl_type%5D=linkedin_company_website)  
17 dipendenti su LinkedIn®

#### Who Uses This Product?

- **Who Uses This:** Student, Data Analyst
- **Top Industries:** Software per computer, Istruzione superiore
- **Company Size:** 67% Small, 25% Medium

#### What Do G2 Reviewers Say About Deepnote?

_AI-generated summary from verified user reviews_

##### Pros

- Gli utenti elogiano la **facilità d'uso** di Deepnote, facilitando la collaborazione e semplificando i compiti di analisi dei dati.
- Gli utenti apprezzano le capacità di **collaborazione senza soluzione di continuità** di Deepnote, migliorando significativamente il lavoro di squadra e l'efficienza dei progetti.
- Gli utenti apprezzano la **collaborazione in tempo reale** in Deepnote, migliorando il lavoro di squadra e l'efficienza nei processi di analisi dei dati.
- Gli utenti apprezzano le **facili integrazioni** in Deepnote, che consentono un flusso di lavoro senza interruzioni e una gestione efficiente dei dati.
- Gli utenti apprezzano la **gestione dei dati facile** in Deepnote, che consente un'integrazione senza soluzione di continuità e analisi collaborative.

##### Cons

- Gli utenti notano **prestazioni lente** con grandi set di dati, influenzando la reattività dell'applicazione e l'agilità dell'analisi.
- Gli utenti trovano che le **funzionalità limitate** di Deepnote ostacolino la sua usabilità e comparabilità con altri strumenti.
- Gli utenti segnalano problemi con la **gestione dei dati** , tra cui lentezza, crash del kernel e navigazione dei file non intuitiva.
- Gli utenti sperimentano **prestazioni lente** con Deepnote, in particolare quando gestiscono grandi set di dati o più richieste.
- Gli utenti spesso sperimentano **tempi di caricamento lenti** in Deepnote, specialmente con progetti più grandi, influenzando la loro efficienza e il loro flusso di lavoro.

#### What Are Recent G2 Reviews of Deepnote?

**["Collaborazione in tempo reale che rende facile il lavoro in laboratorio"](https://www.g2.com/it/survey_responses/deepnote-review-13100282)**

**Rating:** 5.0/5.0 stars

_— Gabriel P._

[Read full review](https://www.g2.com/it/survey_responses/deepnote-review-13100282)

**["Deepnote rende il lavoro di squadra sui dati senza soluzione di continuità con la collaborazione in tempo reale"](https://www.g2.com/it/survey_responses/deepnote-review-13121723)**

**Rating:** 4.5/5.0 stars

_— Ravindra N._

[Read full review](https://www.g2.com/it/survey_responses/deepnote-review-13121723)

#### What Are G2 Users Discussing About Deepnote?

- [How do you use a deep note?](https://www.g2.com/it/discussions/how-do-you-use-a-deep-note)
- [Is Deepnote open source?](https://www.g2.com/it/discussions/is-deepnote-open-source)
- [Deepnote è buono?](https://www.g2.com/it/discussions/is-deepnote-good) - 1 comment
- [Deepnote è migliore di Colab?](https://www.g2.com/it/discussions/is-deepnote-better-than-colab) - 1 comment

### [SAP Analytics Cloud](https://www.g2.com/products/sap-analytics-cloud/reviews)

With the SAP Analytics Cloud solution, you can bring together analytics and planning with unique integration to SAP applications and smooth access to heterogenous data sources. As the analytics and planning solution within SAP Business Technology Platform, SAP Analytics Cloud supports trusted insights and integrated planning processes enterprise-wide to help you make decisions without doubt.

**Average Rating:** 4.2/5.0

**Total Reviews:** 750

#### How Do G2 Users Rate SAP Analytics Cloud?

- **Has the product been a good partner in doing business?:** 8.3/10 (Category avg: 9.1/10)
- **Steps to Answer:** 8.0/10 (Category avg: 8.4/10)
- **Reports Interface:** 8.3/10 (Category avg: 8.7/10)
- **Calculated Fields:** 7.9/10 (Category avg: 8.5/10)

#### Who Is the Company Behind SAP Analytics Cloud?

- **Seller:** [SAP](https://www.g2.com/sellers/sap)
- **Company Website:** www.sap.com
- **Year Founded:** 1972
- **HQ Location:** Walldorf
- **Twitter:** @SAP  
297,052 Twitter followers
- **LinkedIn® Page:** [www.linkedin.com](https://www.g2.com/external_clickthroughs/record?secure%5Bsource_type%5D=product_profile&secure%5Btoken%5D=8fd712dbd816fadfc039a60dcf8c1a3d6a48469756075586fa0be3da7e4b74d7&secure%5Burl%5D=https%3A%2F%2Fwww.linkedin.com%2Fcompany%2Fsap%2F&secure%5Burl_type%5D=linkedin_company_website)  
141,955 employees on LinkedIn®

#### Who Uses This Product?

- **Who Uses This:** Senior Consultant, Consultant
- **Top Industries:** Information Technology and Services, Computer Software
- **Company Size:** 49% Large, 28% Medium

#### What Do G2 Reviewers Say About SAP Analytics Cloud?

_AI-generated summary from verified user reviews_

##### Pros

- Users value the **ease of use** in SAP Analytics Cloud, facilitating effortless data understanding and streamlined reporting.
- Users appreciate the **wide range of data connectivity options** in SAP Analytics Cloud, enhancing integration and analytics capabilities.
- Users value the **interactive dashboards** of SAP Analytics Cloud, which enhance data clarity and user customization.
- Users value the **easy integrations** of SAP Analytics Cloud, enjoying seamless connectivity and efficient data analysis across projects.
- Users appreciate the **wide range of data connectivity and predictive analytics** in SAP Analytics Cloud for effective decision-making.

##### Cons

- Users experience **slow performance** with SAP Analytics Cloud, particularly when working with complex datasets and large models.
- Users face a **steep learning curve** with SAP Analytics Cloud, requiring training to navigate its complex features effectively.
- Users find the **steep learning curve** challenging, especially without guidance for navigating SAP Analytics Cloud's features.
- Users experience significant **performance issues** with SAP Analytics Cloud, particularly with large datasets and complex calculations.
- Users experience **slow performance with large datasets** , making complex analyses cumbersome and time-consuming.

#### What Are Recent G2 Reviews of SAP Analytics Cloud?

**["SAP Analytics Cloud Clean Dashboards and Powerful Real Time Analytics in One Place"](https://www.g2.com/survey_responses/sap-analytics-cloud-review-12817514)**

**Rating:** 5.0/5.0 stars

_— Muzammil M._

[Read full review](https://www.g2.com/survey_responses/sap-analytics-cloud-review-12817514)

**["Reliable & User-Friendly Analytics Tool"](https://www.g2.com/survey_responses/sap-analytics-cloud-review-12885706)**

**Rating:** 4.0/5.0 stars

_— sagar i._

[Read full review](https://www.g2.com/survey_responses/sap-analytics-cloud-review-12885706)

#### What Are G2 Users Discussing About SAP Analytics Cloud?

- [What is SAP Analytics Cloud used for?](https://www.g2.com/discussions/what-is-sap-analytics-cloud-used-for) - 2 comments
- [What is SAP Lumira used for?](https://www.g2.com/discussions/sap-lumira-what-is-sap-lumira-used-for) - 1 comment, 1 upvote
- [What is SAP Analytics Hub used for?](https://www.g2.com/discussions/what-is-sap-analytics-hub-used-for) - 1 comment
- [How does SAP Analytics calculate average cloud?](https://www.g2.com/discussions/how-does-sap-analytics-calculate-average-cloud)
- [What is predictive analytics software?](https://www.g2.com/discussions/sap-predictive-analytics-what-is-predictive-analytics-software) - 1 comment

### [KNIME](https://www.g2.com/it/products/knime-analytics-platform/reviews)

KNIME aiuta tutti a dare un senso ai dati. La sua piattaforma KNIME Analytics, gratuita e open source, consente a chiunque — che provenga da un background aziendale, tecnico o di dati — di lavorare intuitivamente con i dati, ogni giorno. KNIME Business Hub è il complemento commerciale della piattaforma KNIME Analytics e consente agli utenti di collaborare sulla scienza dei dati e condividere approfondimenti all'interno dell'organizzazione. Insieme, i prodotti supportano l'intero ciclo di vita della scienza dei dati, permettendo ai team a tutti i livelli di prontezza analitica di supportare l'operazionalizzazione dei dati e di costruire una pratica di scienza dei dati scalabile.

**Average Rating:** 4.5/5.0

**Total Reviews:** 102

#### How Do G2 Users Rate KNIME?

- **Ritiene che the product sia stato un valido partner commerciale?:** 8.5/10 (Category avg: 9.1/10)
- **Passaggi per rispondere:** 8.3/10 (Category avg: 8.4/10)
- **Interfaccia dei Rapporti:** 8.1/10 (Category avg: 8.7/10)
- **Campi Calcolati:** 8.9/10 (Category avg: 8.5/10)

#### Who Is the Company Behind KNIME?

- **Venditore:** [KNIME](https://www.g2.com/it/sellers/knime)
- **Sito web dell'azienda:** knime.com
- **Anno di Fondazione:** 2008
- **Sede centrale:** Zurich, Switzerland
- **Twitter:** @knime  
7,998 follower su Twitter
- **Pagina LinkedIn®:** [www.linkedin.com](https://www.g2.com/it/external_clickthroughs/record?secure%5Bsource_type%5D=product_profile&secure%5Btoken%5D=f7a516bbe2dc4d0e292ed78e5e957b79bbec1dfe489fa8be92a344d651ca0810&secure%5Burl%5D=https%3A%2F%2Fwww.linkedin.com%2Fcompany%2F692207%3Ftrk%3Dtyah%26trkInfo%3DclickedVertical%253Acompany%252CclickedEntityId%253A692207%252Cidx%253A2-1-4%252CtarId%253A1454002156993%252Ctas%253Aknime&secure%5Burl_type%5D=linkedin_company_website)  
244 dipendenti su LinkedIn®

#### Who Uses This Product?

- **Top Industries:** Tecnologia dell'informazione e servizi, Istruzione superiore
- **Company Size:** 42% Large, 33% Medium

#### What Do G2 Reviewers Say About KNIME?

_AI-generated summary from verified user reviews_

##### Pros

- Gli utenti trovano l' **facilità d'uso** di KNIME eccezionale, permettendo a persone non tecniche di creare flussi di lavoro senza sforzo.
- Gli utenti apprezzano la **facilità di codifica** di KNIME, che consente anche ai non programmatori di creare flussi di lavoro complessi senza sforzo.
- Gli utenti trovano **facile da imparare** KNIME vantaggioso, permettendo ai principianti di iniziare a ottenere risultati rapidamente.
- Gli utenti trovano KNIME una **piattaforma potente e facile da imparare** , che consente un'analisi dei dati efficace e lo sviluppo di soluzioni AI.
- Gli utenti evidenziano le capacità di **visualizzazione dei dati senza sforzo** di KNIME, rendendo i dati complessi accessibili e facili da comprendere.

##### Cons

- Gli utenti trovano **la curva di apprendimento iniziale impegnativa** , soprattutto per coloro che sono nuovi alla scienza dei dati e alla programmazione visiva.
- Gli utenti riscontrano significativi **problemi di utilizzo della memoria** con KNIME, portando a prestazioni lente, specialmente con file di grandi dimensioni.
- Gli utenti segnalano **limitazioni di archiviazione** con KNIME, affrontando problemi di disponibilità di memoria che ostacolano le prestazioni con file di grandi dimensioni.
- Gli utenti notano che i **problemi di gestione dei dati** persistono in KNIME, in particolare con la gestione dei file e la compatibilità con i database.
- Gli utenti sentono che la **mancanza di risorse didattiche** ostacola la loro capacità di sfruttare appieno le potenzialità di KNIME.

#### What Are Recent G2 Reviews of KNIME?

**["I flussi di lavoro visivi di KNIME - Uno dei migliori strumenti per i professionisti di revisione contabile, contabilità e finanza"](https://www.g2.com/it/survey_responses/knime-review-12976842)**

**Rating:** 5.0/5.0 stars

_— Charm M._

[Read full review](https://www.g2.com/it/survey_responses/knime-review-12976842)

**["L'analisi senza codice di KNIME, da descrittiva a AI agentica, con trascinamento e rilascio gratuito"](https://www.g2.com/it/survey_responses/knime-review-12992618)**

**Rating:** 5.0/5.0 stars

_— Guylaine B._

[Read full review](https://www.g2.com/it/survey_responses/knime-review-12992618)

#### What Are G2 Users Discussing About KNIME?

- [A cosa serve la piattaforma KNIME Analytics?](https://www.g2.com/it/discussions/what-is-knime-analytics-platform-used-for)
- [Knime è facile da usare?](https://www.g2.com/it/discussions/is-knime-easy-to-use) - 1 comment
- [How do I use Knime Analytics?](https://www.g2.com/it/discussions/how-do-i-use-knime-analytics)
- [Is Knime any good?](https://www.g2.com/it/discussions/is-knime-any-good)
- [What is Knime analytics platform?](https://www.g2.com/it/discussions/what-is-knime-analytics-platform)

### [Coefficient](https://www.g2.com/products/coefficient/reviews)

Coefficient is a new way to work with your company data better, faster, and more accurately without ever leaving your spreadsheet, integrating with the tools you already use. Install the Coefficient Excel or Google Sheets extension and use it in a new or existing sheet in seconds. Once installed, Coefficient lives as a sidebar companion so your company data is only a couple of clicks away at any time. Any data source that you work with is available directly in your Coefficient sidebar – such as Salesforce, HubSpot, Snowflake, NetSuite, QuickBooks, MySQL, and Looker – with the ability to consolidate your data from multiple systems into one spreadsheet. Use Coefficient filters to easily customize your imports to only work with the data you need, keeping your spreadsheets performant. Quickly go back anytime to add more data in the same report. Never rebuild the same analysis twice by keeping your data up to date with scheduled updates. And, use Coefficient alerts to trigger Slack or email messages anytime your spreadsheet updates. Now, you can turn your spreadsheet into the most flexible, powerful monitoring system across all of your company data. Say “goodbye” to manual data workflows and “hello” to connected spreadsheets.

**Average Rating:** 4.7/5.0

**Total Reviews:** 195

#### How Do G2 Users Rate Coefficient?

- **Has the product been a good partner in doing business?:** 9.0/10 (Category avg: 9.1/10)
- **Reports Interface:** 10.0/10 (Category avg: 8.7/10)
- **Calculated Fields:** 10.0/10 (Category avg: 8.5/10)

#### Who Is the Company Behind Coefficient?

- **Seller:** [Coefficient](https://www.g2.com/sellers/coefficient)
- **Company Website:** coefficient.io
- **Year Founded:** 2020
- **HQ Location:** Palo Alto, CA
- **Twitter:** @coefficient\_io  
346 Twitter followers
- **LinkedIn® Page:** [www.linkedin.com](https://www.g2.com/external_clickthroughs/record?secure%5Bsource_type%5D=product_profile&secure%5Btoken%5D=1a36ef868415520ac840f5699de01e684ba3b9e328d0a3215043fadd7d1bd7ad&secure%5Burl%5D=https%3A%2F%2Fwww.linkedin.com%2Fcompany%2Fcoefficientworks%2F&secure%5Burl_type%5D=linkedin_company_website)  
71 employees on LinkedIn®

#### Who Uses This Product?

- **Top Industries:** Computer Software, Information Technology and Services
- **Company Size:** 46% Medium, 34% Small

#### What Do G2 Reviewers Say About Coefficient?

_AI-generated summary from verified user reviews_

##### Pros

- Users appreciate the **ease of use** with Coefficient, enjoying seamless data extraction and hassle-free connectivity.
- Users love the **automation capabilities** of Coefficient, which simplify data integration and save significant time.
- Users appreciate the **seamless integrations** of Coefficient, effortlessly syncing data between Salesforce, QuickBooks, and Google Sheets.
- Users love the **easy integrations** of Coefficient, drastically improving workflow and enabling hassle-free data syncing.
- Users enjoy the **time-saving automation** of Coefficient, regaining hours each week with effortless data management.

##### Cons

- Users find the **feature limitations** of Coefficient frustrating, especially with filtering and data formatting issues.
- Users face **limited features** with Coefficient, particularly regarding filter and import restrictions compared to Google Sheets.
- Users are dissatisfied with the **missing features** in Coefficient, such as limited filter options and inadequate chart integration.
- Users face **filter limitations** in Coefficient, impacting their ability to manage data efficiently across imports.
- Users face **integration issues** with Coefficient, particularly lacking essential features and facing frustrating import formats.

#### What Are Recent G2 Reviews of Coefficient?

**["Seamless Database Queries in Google Sheets with Responsive Support"](https://www.g2.com/survey_responses/coefficient-review-13098229)**

**Rating:** 4.5/5.0 stars

_— Verified User in Marketing and Advertising_

[Read full review](https://www.g2.com/survey_responses/coefficient-review-13098229)

**["Efficient, User-Friendly Tool for Integrating Salesforce with Google Sheets"](https://www.g2.com/survey_responses/coefficient-review-12701723)**

**Rating:** 5.0/5.0 stars

_— Ellen Dericks C._

[Read full review](https://www.g2.com/survey_responses/coefficient-review-12701723)

### [Lightdash](https://www.g2.com/products/lightdash/reviews)

Lightdash is the fastest way for modern data teams to build and scale AI-powered self-serve analytics. It enables analysts to define metrics and make them accessible to non-technical users, who can explore data and build dashboards without writing SQL. Lightdash integrates with modern data stacks, supports a governed semantic layer, and offers developer-friendly features like Git-based workflows. It is designed to reduce the overhead of maintaining BI tools, streamline metric definitions, and improve access to consistent data across teams. Lightdash is used and trusted by companies of all sizes, from start ups to international publicly listed organisations.

**Average Rating:** 4.9/5.0

**Total Reviews:** 19

#### How Do G2 Users Rate Lightdash?

- **Has the product been a good partner in doing business?:** 10.0/10 (Category avg: 9.1/10)
- **Steps to Answer:** 8.1/10 (Category avg: 8.4/10)
- **Reports Interface:** 9.4/10 (Category avg: 8.7/10)
- **Calculated Fields:** 8.3/10 (Category avg: 8.5/10)

#### Who Is the Company Behind Lightdash?

- **Seller:** [Lightdash](https://www.g2.com/sellers/lightdash)
- **HQ Location:** San Francisco, US
- **Twitter:** @lightdash\_devs  
2,416 Twitter followers
- **LinkedIn® Page:** [www.linkedin.com](https://www.g2.com/external_clickthroughs/record?secure%5Bsource_type%5D=product_profile&secure%5Btoken%5D=dd708d86fee7e058d7253b4a21e1d60a688c90c33fdcfc79dc18c329d1b5e09c&secure%5Burl%5D=https%3A%2F%2Fwww.linkedin.com%2Fcompany%2Flightdash%2F&secure%5Burl_type%5D=linkedin_company_website)  
29 employees on LinkedIn®

#### Who Uses This Product?

- **Company Size:** 58% Medium, 21% Large

#### What Are Recent G2 Reviews of Lightdash?

**["Lightdash: Lightning-Fast dbt-Powered BI with Rapid Feature Releases"](https://www.g2.com/survey_responses/lightdash-review-12586837)**

**Rating:** 5.0/5.0 stars

_— Moritz V._

[Read full review](https://www.g2.com/survey_responses/lightdash-review-12586837)

**["Precise Data Insights, Minor Clunky Aspects"](https://www.g2.com/survey_responses/lightdash-review-12669063)**

**Rating:** 4.5/5.0 stars

_— Alice P._

[Read full review](https://www.g2.com/survey_responses/lightdash-review-12669063)

### [Luzmo](https://www.g2.com/products/luzmo/reviews)

Luzmo helps businesses embed data products hassle-free, empowering their users with fast, confident decisions in record time.

**Average Rating:** 4.6/5.0

**Total Reviews:** 70

#### How Do G2 Users Rate Luzmo?

- **Has the product been a good partner in doing business?:** 9.4/10 (Category avg: 9.1/10)
- **Steps to Answer:** 8.2/10 (Category avg: 8.4/10)
- **Reports Interface:** 8.8/10 (Category avg: 8.7/10)
- **Calculated Fields:** 8.1/10 (Category avg: 8.5/10)

#### Who Is the Company Behind Luzmo?

- **Seller:** [Luzmo NV](https://www.g2.com/sellers/luzmo-nv)
- **Year Founded:** 2015
- **HQ Location:** Brooklyn, US
- **Twitter:** @luzmo\_official  
895 Twitter followers
- **LinkedIn® Page:** [www.linkedin.com](https://www.g2.com/external_clickthroughs/record?secure%5Bsource_type%5D=product_profile&secure%5Btoken%5D=d225d4544e9582bc94836bf9a260ea1afd86c53d8d59f73f4504786a1521c939&secure%5Burl%5D=https%3A%2F%2Fwww.linkedin.com%2Fcompany%2F10198259%2F&secure%5Burl_type%5D=linkedin_company_website)  
50 employees on LinkedIn®

#### Who Uses This Product?

- **Who Uses This:** CEO
- **Top Industries:** Computer Software, Information Technology and Services
- **Company Size:** 59% Small, 32% Medium

#### What Do G2 Reviewers Say About Luzmo?

_AI-generated summary from verified user reviews_

##### Pros

- Users appreciate the **intuitive ease of use** of Luzmo, enabling quick adoption and fast dashboard creation.
- Users are impressed by Luzmo's **embedding features** , enabling quick insights and seamless integration into their SaaS applications.
- Users value the **customization features** of Luzmo, enabling tailored applications and efficient management across diverse client environments.
- Users commend Luzmo for its **intuitive interface and rapid deployment** , enabling quick insights and analytics integration.
- Users praise the **easy setup** of Luzmo, enabling swift adoption and fast deployment of analytics tools.

##### Cons

- Users find Luzmo's **complexity challenging** , with setup difficulties and limited querying capabilities hindering efficiency.
- Users are disappointed by Luzmo's **limited options** for complex queries and insufficient chart functionality.
- Users note **performance issues** with large datasets and lag in the interface, affecting overall workflow experience.
- Users experience **table limitations** with Luzmo, hindering complex queries and causing challenges with data handling.
- Users experience **performance and sync issues** with Luzmo, especially when handling larger datasets, impacting usability.

#### What Are Recent G2 Reviews of Luzmo?

**["Powerful Embedded BI with Proactive Support Addressing Performance at Scale"](https://www.g2.com/survey_responses/luzmo-review-12246440)**

**Rating:** 4.5/5.0 stars

_— Verified User in Logistics and Supply Chain_

[Read full review](https://www.g2.com/survey_responses/luzmo-review-12246440)

**["Fast, Beautiful Dashboards and Effortless Embedding"](https://www.g2.com/survey_responses/luzmo-review-11991075)**

**Rating:** 4.5/5.0 stars

_— Shanti B._

[Read full review](https://www.g2.com/survey_responses/luzmo-review-11991075)

#### What Are G2 Users Discussing About Luzmo?

- [What is Cumul.io used for?](https://www.g2.com/discussions/what-is-cumul-io-used-for)

### [Knowi](https://www.g2.com/products/knowi/reviews)

Knowi is an end-to-end AI-powered analytics platform designed for modern data, enabling enterprises of all sizes to dramatically accelerate the journey from raw data to actionable insights. With native integration to virtually any data source—including SQL, NoSQL (MongoDB, Elasticsearch, InfluxDB), REST APIs, cloud databases, and documents—Knowi eliminates the need for complex data transformation processes required by alternative solutions. Data teams can integrate, blend, visualize, and analyze data from any source 10X faster, all within a single platform. They can then leverage AI to uncover insights, embed analytics into applications, share dashboards with business users, and automate reporting.

**Average Rating:** 4.9/5.0

**Total Reviews:** 27

#### How Do G2 Users Rate Knowi?

- **Has the product been a good partner in doing business?:** 9.7/10 (Category avg: 9.1/10)
- **Steps to Answer:** 9.3/10 (Category avg: 8.4/10)
- **Reports Interface:** 9.7/10 (Category avg: 8.7/10)
- **Calculated Fields:** 9.0/10 (Category avg: 8.5/10)

#### Who Is the Company Behind Knowi?

- **Seller:** [Knowi](https://www.g2.com/sellers/knowi)
- **Year Founded:** 2015
- **HQ Location:** Oakland, California
- **Twitter:** @knowico  
2,636 Twitter followers
- **LinkedIn® Page:** [www.linkedin.com](https://www.g2.com/external_clickthroughs/record?secure%5Bsource_type%5D=product_profile&secure%5Btoken%5D=61ad6fa1581f1b8c0daf229ae53df829f1526520a28e14f74ac3121af71ff6d6&secure%5Burl%5D=https%3A%2F%2Fwww.linkedin.com%2Fcompany%2F3675224%2F&secure%5Burl_type%5D=linkedin_company_website)  
23 employees on LinkedIn®

#### Who Uses This Product?

- **Company Size:** 46% Small, 39% Medium

#### What Do G2 Reviewers Say About Knowi?

_AI-generated summary from verified user reviews_

##### Pros

- Users praise Knowi's **exceptional customer support** , highlighting quick responses and tailored assistance throughout their onboarding process.
- Users commend Knowi for its **exceptional onboarding experience** , ensuring a seamless transition and tailored guidance for success.
- Users appreciate the **AI-driven analytics** of Knowi, enhancing data connections and reporting with proactive support.
- Users value the **automation capabilities** of Knowi, streamlining reporting and drastically reducing manual data management efforts.
- Users value the **ease of use** of Knowi, appreciating intuitive dashboards and excellent onboarding support for a quick start.

##### Cons

- Users find the **learning curve steep** , especially for advanced features and complex data integration with Knowi.
- Users find a **lack of guidance** for API connections challenging, making initial setup time-consuming with Knowi.
- Users feel the **lack of tutorials** for API connections in Knowi makes initial setup time-consuming and challenging.

#### What Are Recent G2 Reviews of Knowi?

**["Intuitive Dashboarding with Exceptional Support"](https://www.g2.com/survey_responses/knowi-review-12378559)**

**Rating:** 5.0/5.0 stars

_— Jose D._

[Read full review](https://www.g2.com/survey_responses/knowi-review-12378559)

**["One analytics layer across our SQL and NoSQL data and now Al our customers can use"](https://www.g2.com/survey_responses/knowi-review-13186089)**

**Rating:** 5.0/5.0 stars

_— Michael S._

[Read full review](https://www.g2.com/survey_responses/knowi-review-13186089)

### [Teradata Autonomous Knowledge Platform](https://www.g2.com/products/teradata-autonomous-knowledge-platform/reviews)

Teradata Autonomous Knowledge Platform activates enterprise intelligence by unifying data, knowledge and business context to achieve tangible outcomes. With Teradata, organizations can provide agents with full context for impact when it matters. Our solution lets businesses connect and scale on premises, in the cloud, or through a hybrid approach. Teradata delivers real business value with AI. Learn more at Teradata.com.

**Average Rating:** 4.3/5.0

**Total Reviews:** 356

#### How Do G2 Users Rate Teradata Autonomous Knowledge Platform?

- **Has the product been a good partner in doing business?:** 8.2/10 (Category avg: 9.1/10)
- **Steps to Answer:** 8.1/10 (Category avg: 8.4/10)
- **Reports Interface:** 7.7/10 (Category avg: 8.7/10)
- **Calculated Fields:** 8.4/10 (Category avg: 8.5/10)

#### Who Is the Company Behind Teradata Autonomous Knowledge Platform?

- **Seller:** [Teradata Autonomous Knowledge Platform](https://www.g2.com/sellers/teradata-autonomous-knowledge-platform)
- **Year Founded:** 1979
- **HQ Location:** San Diego, CA
- **Twitter:** @Teradata  
93,113 Twitter followers
- **LinkedIn® Page:** [www.linkedin.com](https://www.g2.com/external_clickthroughs/record?secure%5Bsource_type%5D=product_profile&secure%5Btoken%5D=06895b9a8db4fa478ba7da480ccd214a14ef698abd028e4642e62f189e82b650&secure%5Burl%5D=https%3A%2F%2Fwww.linkedin.com%2Fcompany%2F1466%2F&secure%5Burl_type%5D=linkedin_company_website)  
9,901 employees on LinkedIn®
- **Ownership:** NYSE:TDC

#### Who Uses This Product?

- **Who Uses This:** Data Engineer, Software Engineer
- **Top Industries:** Information Technology and Services, Financial Services
- **Company Size:** 69% Large, 22% Medium

#### What Do G2 Reviewers Say About Teradata Autonomous Knowledge Platform?

_AI-generated summary from verified user reviews_

##### Pros

- Users highlight the **extreme performance** of the Teradata Autonomous Knowledge Platform, especially for processing large data volumes efficiently.
- Users value the **high performance query execution** in Teradata, enhancing their business analytics capabilities significantly.
- Users value the **scalability** of Teradata Autonomous Knowledge Platform, enhancing data integration and operational efficiency significantly.
- Users commend the **high performance and speed** of Teradata, efficiently processing large datasets without issues.
- Users value the **fast processing of large datasets** with Teradata, praising its performance and stability during operations.

##### Cons

- Users find the **steep learning curve** of Teradata Autonomous Knowledge Platform challenging, impacting adoption and productivity temporarily.
- Users find the **steep learning curve** of Teradata Autonomous Knowledge Platform challenging, particularly for those lacking technical expertise.
- Users find the **complexity** of Teradata's platform challenging, particularly for non-technical users and new adopters.
- Users express concerns over the **cost management requirements** needed to avoid potential misusage and performance issues.
- Users feel the **high cost** of Teradata Autonomous Knowledge Platform is a significant drawback affecting accessibility.

#### What Are Recent G2 Reviews of Teradata Autonomous Knowledge Platform?

**["Teradata Vantage Fast Query Performance and Strong Analytics for Big Data"](https://www.g2.com/survey_responses/teradata-autonomous-knowledge-platform-review-12821668)**

**Rating:** 5.0/5.0 stars

_— Muzammil M._

[Read full review](https://www.g2.com/survey_responses/teradata-autonomous-knowledge-platform-review-12821668)

**["Teradata Vantage Excels at Big Data Processing and Advanced Analytics"](https://www.g2.com/survey_responses/teradata-autonomous-knowledge-platform-review-12739181)**

**Rating:** 4.5/5.0 stars

_— Nijat I._

[Read full review](https://www.g2.com/survey_responses/teradata-autonomous-knowledge-platform-review-12739181)

#### What Are G2 Users Discussing About Teradata Autonomous Knowledge Platform?

- [What does Teradata Data Lab do?](https://www.g2.com/discussions/what-does-teradata-data-lab-do)
- [Is Teradata a premiership?](https://www.g2.com/discussions/is-teradata-a-premiership)
- [What is Teradata Vantage?](https://www.g2.com/discussions/what-is-teradata-vantage)
- [How much does Teradata cost?](https://www.g2.com/discussions/how-much-does-teradata-cost)
- [What is Sandbox in Teradata?](https://www.g2.com/discussions/what-is-sandbox-in-teradata)

### [SAS Enterprise Guide](https://www.g2.com/products/sas-enterprise-guide/reviews)

SAS Enterprise Guide is a Windows-based client application that provides a user-friendly, point-and-click interface to the powerful analytics capabilities of SAS software. Designed to cater to both novice and experienced users, it facilitates data access, management, analysis, and reporting without the need for extensive programming knowledge. By integrating a wide array of analytical tasks with an intuitive graphical interface, SAS Enterprise Guide empowers users to efficiently conduct complex analyses and share results across their organization. Key Features and Functionality: - Intuitive Interface and Wizards: Offers guided access to SAS capabilities, from basic reporting to advanced analyses, through flexible wizards and an intuitive process flow diagram facility. - Comprehensive Analytical Tasks: Includes over 100 prebuilt tasks for descriptive statistics, predictive modeling, regression analysis, and more, enabling users to perform complex analyses without writing code. - Data Management: Provides a powerful graphical query builder for accessing and manipulating various data types, including SAS datasets and native Windows data types, without requiring SQL expertise. - OLAP Access and Visualization: Supports dynamic slicing, drilling, and pivoting of data for exploration, with integration capabilities for SAS OLAP Server and other third-party vendors supporting OLE DB for OLAP. - Result Distribution and Sharing: Facilitates the distribution of results through multiple channels, including SAS BI report/content repository, Microsoft Office documents, and email, ensuring seamless sharing and collaboration. - High-Performance Computing and Grid Enablement: Automatically detects grid environments for efficient processing, analyzes SAS programs to optimize performance, and enables parallel execution of tasks on the same server. Primary Value and User Solutions: SAS Enterprise Guide addresses the need for a self-service analytics environment that empowers business analysts and other users to perform sophisticated data analyses without relying heavily on IT departments. By providing guided access to data integration, preparation, analytics, and reporting, it enables users to quickly access data, conduct analyses, and distribute results, thereby accelerating decision-making processes. The integration with SAS Viya further enhances its capabilities, allowing users to leverage modern, cloud-based platforms for scalable and efficient analytics. This comprehensive toolset ultimately helps organizations harness their data effectively, leading to more informed business decisions and improved operational efficiency.

**Average Rating:** 4.3/5.0

**Total Reviews:** 112

#### How Do G2 Users Rate SAS Enterprise Guide?

- **Has the product been a good partner in doing business?:** 9.0/10 (Category avg: 9.1/10)
- **Steps to Answer:** 7.9/10 (Category avg: 8.4/10)
- **Reports Interface:** 8.4/10 (Category avg: 8.7/10)
- **Calculated Fields:** 8.1/10 (Category avg: 8.5/10)

#### Who Is the Company Behind SAS Enterprise Guide?

- **Seller:** [SAS Institute Inc.](https://www.g2.com/sellers/sas-institute-inc-df6dde22-a5e5-4913-8b21-4fa0c6c5c7c2)
- **Year Founded:** 1976
- **HQ Location:** Cary, NC
- **Twitter:** @SASsoftware  
60,863 Twitter followers
- **LinkedIn® Page:** [www.linkedin.com](https://www.g2.com/external_clickthroughs/record?secure%5Bsource_type%5D=product_profile&secure%5Btoken%5D=64db42c044af5bbad79bd9677a620a6c31a8ff1abf4e7b2a6f1d6ed9561d105d&secure%5Burl%5D=https%3A%2F%2Fwww.linkedin.com%2Fcompany%2F1491%2F&secure%5Burl_type%5D=linkedin_company_website)  
18,638 employees on LinkedIn®
- **Phone:** 1-800-727-0025

#### Who Uses This Product?

- **Top Industries:** Banking, Hospital & Health Care
- **Company Size:** 57% Large, 26% Medium

#### What Do G2 Reviewers Say About SAS Enterprise Guide?

_AI-generated summary from verified user reviews_

##### Pros

- Users appreciate the **ease of use** in SAS Enterprise Guide, finding it accessible for beginners and non-technical users.
- Users enjoy the **flexible user interface** of SAS Enterprise Guide, combining coding freedom with intuitive GUI features.
- Users value the **efficient data analysis** capabilities of SAS Enterprise Guide, enhancing decision-making through integrated tools.
- Users value the **effective data visualization** capabilities of SAS Enterprise Guide, enhancing decision-making with ease.
- Users find SAS Enterprise Guide's **ease of learning** excellent, accommodating everyone from beginners to experts effectively.

##### Cons

- Users experience **slow performance** with SAS Enterprise Guide, making data manipulation and debugging cumbersome.
- Users find the **complex usage** challenging, especially first-time navigation and finding options within the menus.
- Users find the **learning curve steep** due to a clunky interface and complicated menu navigation.
- Users often find SAS Enterprise Guide **buggy and slow** , making data manipulation a challenging experience.
- Users often struggle with **integration issues** , finding it hard to connect SAS Enterprise Guide to various systems.

#### What Are Recent G2 Reviews of SAS Enterprise Guide?

**["Dynamic and User-Friendly with Robust Performance"](https://www.g2.com/survey_responses/sas-enterprise-guide-review-12706111)**

**Rating:** 4.5/5.0 stars

_— Charles A._

[Read full review](https://www.g2.com/survey_responses/sas-enterprise-guide-review-12706111)

**["Versatile Tool with Room for UI Improvement"](https://www.g2.com/survey_responses/sas-enterprise-guide-review-12713363)**

**Rating:** 5.0/5.0 stars

_— Alec E._

[Read full review](https://www.g2.com/survey_responses/sas-enterprise-guide-review-12713363)

#### What Are G2 Users Discussing About SAS Enterprise Guide?

- [What is SAS Enterprise Guide used for?](https://www.g2.com/discussions/sas-enterprise-guide-what-is-sas-enterprise-guide-used-for)
- [How much is SAS Enterprise Guide?](https://www.g2.com/discussions/how-much-is-sas-enterprise-guide)
- [What is the latest version of SAS Enterprise Guide?](https://www.g2.com/discussions/what-is-the-latest-version-of-sas-enterprise-guide)
- [What is the difference between SAS Studio and SAS Enterprise Guide?](https://www.g2.com/discussions/what-is-the-difference-between-sas-studio-and-sas-enterprise-guide)
- [What is SAS Enterprise Guide used for?](https://www.g2.com/discussions/what-is-sas-enterprise-guide-used-for)

### [Splunk Enterprise](https://www.g2.com/it/products/splunk-enterprise/reviews)

Scopri cosa sta succedendo nella tua azienda e prendi rapidamente azioni significative con Splunk Enterprise. Automatizza la raccolta, l'indicizzazione e l'allerta dei dati macchina che sono critici per le tue operazioni. Scopri le intuizioni attuabili da tutti i tuoi dati, indipendentemente dalla fonte o dal formato. Sfrutta l'intelligenza artificiale e l'apprendimento automatico per decisioni aziendali predittive e proattive.

**Average Rating:** 4.3/5.0

**Total Reviews:** 415

#### How Do G2 Users Rate Splunk Enterprise?

- **Ritiene che the product sia stato un valido partner commerciale?:** 8.7/10 (Category avg: 9.1/10)
- **Interfaccia dei Rapporti:** 5.0/10 (Category avg: 8.7/10)
- **Campi Calcolati:** 8.3/10 (Category avg: 8.5/10)

#### Who Is the Company Behind Splunk Enterprise?

- **Venditore:** [Cisco](https://www.g2.com/it/sellers/cisco)
- **Anno di Fondazione:** 1984
- **Sede centrale:** San Jose, CA
- **Twitter:** @Cisco  
720,366 follower su Twitter
- **Pagina LinkedIn®:** [www.linkedin.com](https://www.g2.com/it/external_clickthroughs/record?secure%5Bsource_type%5D=product_profile&secure%5Btoken%5D=476aeabc5a712d049453edd5c54ea0318890d9e60d93782e37fe028224df1cbd&secure%5Burl%5D=https%3A%2F%2Fwww.linkedin.com%2Fcompany%2Fcisco%2F&secure%5Burl_type%5D=linkedin_company_website)  
95,545 dipendenti su LinkedIn®
- **Proprietà:** NASDAQ:CSCO

#### Who Uses This Product?

- **Who Uses This:** Software Engineer, Senior Software Engineer
- **Top Industries:** Tecnologia dell'informazione e servizi, Software per computer
- **Company Size:** 64% Large, 27% Medium

#### What Do G2 Reviewers Say About Splunk Enterprise?

_AI-generated summary from verified user reviews_

##### Pros

- Gli utenti apprezzano l' **innovazione** di Splunk Enterprise, apprezzando le sue funzionalità intuitive e le potenti capacità analitiche.
- Gli utenti apprezzano le **funzionalità di personalizzazione** di Splunk Enterprise, che consentono approfondimenti su misura e dashboard dinamici per un monitoraggio efficace.
- Gli utenti elogiano la **facilità d'uso** di Splunk Enterprise, migliorando il monitoraggio efficace e la rapida risoluzione dei problemi.
- Gli utenti apprezzano le **capacità di gestione dei log efficienti** di Splunk Enterprise per un'analisi accurata e approfondimenti.
- Gli utenti apprezzano le **potenti funzionalità di reporting** di Splunk Enterprise, migliorando significativamente le capacità di analisi e visualizzazione dei dati.

##### Cons

- Gli utenti trovano Splunk Enterprise **costoso** , specialmente con l'aumento dei volumi di dati, influenzando le operazioni dei team più piccoli.
- Gli utenti affrontano una **ripida curva di apprendimento** con Splunk Enterprise, che può ostacolare una rapida padronanza delle sue funzionalità.
- Gli utenti evidenziano la **costosa licenza** di Splunk Enterprise, rendendo difficile l'adozione per alcune aziende.
- Gli utenti affrontano **problemi di integrazione** con Splunk Enterprise, richiedendo migliori componenti aggiuntivi e un'architettura più semplice per una distribuzione più facile.
- Gli utenti ritengono che Splunk Enterprise abbia **funzionalità mancanti** , manchi di componenti aggiuntivi importanti e opzioni di onboarding dei dati più flessibili.

#### What Are Recent G2 Reviews of Splunk Enterprise?

**["Eccellente soluzione di osservabilità aziendale e gestione dei log per infrastrutture cloud ibride"](https://www.g2.com/it/survey_responses/splunk-enterprise-review-12045230)**

**Rating:** 4.5/5.0 stars

_— RaviShankar S._

[Read full review](https://www.g2.com/it/survey_responses/splunk-enterprise-review-12045230)

**["La ricerca SPL e le dashboard sono davvero utili"](https://www.g2.com/it/survey_responses/splunk-enterprise-review-12547655)**

**Rating:** 4.0/5.0 stars

_— Nishith J._

[Read full review](https://www.g2.com/it/survey_responses/splunk-enterprise-review-12547655)

#### What Are G2 Users Discussing About Splunk Enterprise?

- [A cosa serve Splunk Enterprise?](https://www.g2.com/it/discussions/what-is-splunk-enterprise-used-for) - 1 comment
- [Qual è la differenza tra Splunk Enterprise e Splunk Enterprise Security?](https://www.g2.com/it/discussions/splunk-enterprise-what-is-the-difference-between-splunk-enterprise-and-splunk-enterprise-security) - 1 comment
- [Quali sono i componenti di Splunk Enterprise?](https://www.g2.com/it/discussions/what-are-splunk-enterprise-components) - 1 comment
- [Quali app sono incluse con Splunk Enterprise?](https://www.g2.com/it/discussions/which-apps-ship-with-splunk-enterprise) - 1 comment
- [Cosa fa Splunk Enterprise?](https://www.g2.com/it/discussions/what-does-splunk-enterprise-do) - 1 comment

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[Browse Analytics Platforms Themes](/categories/analytics-platforms/themes)

 ![Tian Lin](/assets/transparent-ad5be28fbcd25b7b08d2cebe1d957125437fb5407d75ee717965ad22c8808791.gif "Tian Lin")
TL

Researched and written by [Tian Lin](https://research.g2.com/insights/author/tian-lin)

Updated July 2, 2025

Analytics platforms provide a tool set for businesses to transform raw data into meaningful, actionable insights. They enable organizations to explore data, uncover trends, forecast future outcomes, and support informed decision making.

Unlike tools limited to reporting on past performance, analytics platforms often include advanced capabilities such as predictive modeling, statistical analysis, and machine learning (ML). These platforms are designed to be flexible and scalable, supporting a wide range of use cases across the business.

These platforms are used in nearly every business function, from marketing and sales to finance, operations, and HR, supporting both strategic planning and day-to-day performance monitoring. From data analysts and scientists to business stakeholders and executives, analytics platforms are used by a wide range of personas. While analysts focus on exploring data and generating insights, self-service tools now enable non-technical users to interact directly with data. IT teams support platform integration and security, reflecting the growing push to democratize data access and embed analytics into daily decision-making across the organization.

Analytics platforms support critical functions such as data blending and modeling, enabling users to combine data from diverse sources and build robust, interconnected data models. The visual outputs — dashboards, reports, and interactive charts — help users explore trends, drill down into granular details, and communicate insights clearly.

Unlike standalone data visualization tools, which are limited to presenting information, analytics platforms encompass the full analytical workflow. Many also offer advanced capabilities such as embedded analytics, natural language query, and augmented analytics, which leverage ML to automate insight discovery and make data exploration more accessible to a broader audience.

Analytics platforms and [business intelligence (BI) software](https://www.g2.com/categories/business-intelligence) often work in tandem to support data-driven organizations. While BI tools focus on tracking and reporting historical performance through dashboards and key performance indicators (KPI), analytics platforms provide broader capabilities that support exploratory analysis and strategic planning. BI answers "what happened," while analytics platforms help users understand why it happened and what might happen next. Rather than replacing BI, analytics platforms complement it by enabling deeper insights and empowering a wider range of users across the organization.

To qualify for inclusion in the Analytics Platforms category, a product must:

- Ingest and integrate data from a wide range of structured and semi-structured sources
- Prepare and transform data using built-in tools for cleaning, enrichment, and formatting
- Support connections to diverse data sources, including file uploads, databases, application programming interfaces (API), and SaaS apps
- Enable users to model data relationships, join datasets, and explore data interactively
- Offer tools to build meaningful business reports, dashboards, and visualizations
- Allow creation and sharing of internal analytics applications or embedded insights across teams

Show More

* * *

## How Do You Choose the Right Analytics Platforms?

### What You Should Know About Analytics Platforms

### What are analytics software platforms?

Analytics platforms, also known as business intelligence (BI) platforms, enable companies to gain visibility into their data through data integration, cleansing, blending, enrichment, discovery, and more. These tools are robust systems that sometimes require IT and data science skills to access and decipher company data through custom queries. 

Analytics platforms offer a comprehensive look into a company’s data by pulling from structured and unstructured data sources through detailed queries. Casual business users also benefit from analytics platforms, which offer customizable dashboards and the ability to drill into particular data points and trends.

### What types of analytics tools and platforms exist?

#### **All-in-one software**

##### **Self-service analytics platforms**

Self-service analytics platforms do not require coding knowledge, so business end users can use them for data needs. Cloud-based business analytics software often provides drag-and-drop functionality for building dashboards, prebuilt templates for querying data, and, occasionally, natural language querying for data discovery. 

##### **Embedded BI software**

Embedded BI software can integrate proprietary analytics functionality within other business applications. Businesses may choose an embedded product to promote user adoption; by placing the analytics inside regularly used software, companies enable employees to take advantage of available data. These solutions provide self-service functionality so average business end users can use data for improved decision-making.

#### **Point solutions**

##### **Root cause analysis**

Companies of all sizes produce vast amounts of data from a host of different sources. It can be difficult to keep track of the ebbs and flows of data and to spot outliers and trends across tens if not hundreds (sometimes even thousands) of data sources. Some solutions provide the user with a bird' s-eye view of their data and intelligently alert them to changes in real time. Once alerted, they are able to dive in to evaluate the situation and solve it.

### What are the common features of analytics solutions?

Analytics software platforms are a great aid to any organization needing timely data visualization of high-level analytics. The following are some core features within analytics platforms that can help users make the most of them:

**Data preparation:**  Although standalone [data preparation software](https://www.g2.com/categories/data-preparation) exists that assists in discovering, blending, combining, cleansing, and enriching data—so large datasets can be easily integrated, consumed, and analyzed—analytics platforms must incorporate these functionalities into their core offering. In particular, analytics platforms must support data blending and modeling, allowing the end user to combine data across different databases and other data sources and to develop robust data models of this data. This is a critical step in making meaning out of the chaos by combining data from various sources.

**Data management:** Once the data is properly integrated, it must be managed. This includes restricting data access to certain users, for example. Although some companies opt for a standalone data management solution, such as a data warehouse, analytics platforms must, by definition, provide some level of data management.

**Data modeling and blending:** As mentioned, it is not efficient and often not effective to examine data when it is sprawled across many systems. As a business cloud, analytics platforms help businesses consolidate data and combine data points to understand the relationship between data and derive deep insights.

**Reports and dashboards:** Multilayered, real-time dashboards are a central feature of analytics platforms. Users can program their analytics software to display metrics of their choice and create multiple dashboards that show analytics related to specific teams or initiatives. From predictive website traffic analytics to customer conversion rates over a specified period, users can choose their preferred metrics to feature in dashboards and create as many dashboards as necessary. 

Administrators can adjust the permissions of different dashboards so they are accessible to the users in the company who need them the most. Users can share specific dashboards on office monitors or take screengrabs of dashboards to save and share as needed. Some analytics platform products may allow users to explore dashboards on their mobile devices.

[**Self service**](https://www.g2.com/categories/analytics-platforms/f/self-service) **:** Organizations use these tools to build interactive dashboards for discovering actionable insights. This enables business users like sales representatives, human resource managers, marketers, and other non-data team members to make decisions based on relevant business data.

**Advanced analytics:** Many analytics solutions are incorporating advanced features, sometimes called augmented analytics, to better understand a business’s data, even without IT support. These can include predictive analytics capabilities and data discovery, which includes intelligent suggestions for data visualization and machine learning-powered suggestions for deeper insights.

Other features include [Anomaly detection](https://www.g2.com/categories/analytics-platforms/f/anomaly-detection), [Query based](https://www.g2.com/categories/analytics-platforms/f/query-based), [Search](https://www.g2.com/categories/analytics-platforms/f/search), [Traditional](https://www.g2.com/categories/analytics-platforms/f/traditional)

### What are the benefits of using analytics platforms?

**Replace old or disparate software:** Businesses can replace outdated data storage solutions and reporting tools and migrate to an all-inclusive business cloud as an analytics platform. However, data migration is not essential for deploying an analytics solution, as businesses may not have the time or resources to do so. Therefore, it should be noted that these platforms can integrate with a whole host of solutions, such as [enterprise resource planning (ERP)](https://www.g2.com/categories/erp-systems) and [customer relationship management (CRM) software](https://www.g2.com/categories/crm).

**Improve productivity:** The days of sorting through tens, if not hundreds, of systems and needing immense support from IT have passed. With analytics platforms (especially those that are self-service and have features such as natural language search), anyone looking for data and data analysis, including average business users, can derive insights from their data.

**Save time (automation):** For most analytics platforms, users no longer need a strong background in query languages. Instead, data discovery and root cause analysis allow users to automatically receive alerts and insights into their data and get notified if the data has changed meaningfully.

**Reduce errors:** Although standalone data preparation tools may be the right solution for businesses with particularly complex data, analytics platforms allow users to clean and prepare their data through data mapping and deduplication methods.

**Consolidate data:** In this data-driven era, essentially every program and device a business has produces massive data. To understand this diverse data in the best way possible, combining it through methods such as data blending, which allows users to integrate data from multiple sources into a functioning dataset, is often necessary.

**Improve processes:** Without an analytics platform to be used across a business, processes can be slow and inefficient as interested parties seek data from disparate sources and request data from various people. Analytics platforms can help a business user quickly access data and data analysis and share it with internal and external stakeholders.

### **Who uses analytics tools?**

Analytics platforms can have both internal and external users. 

#### **Internal users**

**Data analysts and data scientists:** These employees are generally the power users of analytics tools, creating complex queries inside the platforms to gather a deeper understanding of business-critical data. These teams may also be tasked with building self-service dashboards to distribute to other teams.

**Sales teams:** Sales teams use self-service analytics tools and embedded analytics solutions to obtain insights into prospective accounts, sales performance, and pipeline forecasting, among many other use cases. Using analytics tools in a sales team can help businesses optimize their sales processes and influence revenue.

**Marketing teams:** Marketing teams often run different types of campaigns, including email marketing, digital advertising, or even traditional advertising campaigns. Analytics tools allow marketing teams to track the performance of those campaigns in one central location.

**Finance teams:** Finance teams leverage analytics software to gain insight into the factors impacting an organization's bottom line. By integrating financial data with sales, marketing, and other operations data, accounting and finance teams pull actionable insights that might not have been uncovered using traditional tools.

**Operations and supply chain teams:** Analytics solutions often utilize a company's ERP system as a data source. These applications track everything from accounting to supply chain and distribution; supply chain managers can optimize several processes to save time and resources by inputting supply chain data into an analytics platform. 

#### **External users**

**Consultants:** Businesses, especially larger ones, do not always understand the breadth and depth of their data, perhaps not even knowing where to begin. An external consultant wielding a powerful analytics platform can help businesses better understand their data and, as a result, make more informed business decisions. 

Users may consider contacting [BI consulting partners](https://www.g2.com/categories/business-intelligence-bi-consulting) to help determine the most relevant analytics and data to capture about their company’s overall success. Following a proper consultation, these agencies may offer assistance with setting up or choosing BI tools. A number of these agencies can assist businesses with the entire BI process, from complete data analysis to the shaping of processes or protocols related to data collection. A relationship with these consultants can prove highly beneficial for users who have never performed data analysis before or want to optimize their company’s reporting.

**Partners:** Partnerships between companies often involve data sharing and cross-company collaboration. As a result, a centralized repository of data, which would allow for data management, data querying, and data insights, can provide an essential tool for these businesses to succeed together, providing them with a birds-eye view of their data.

### **What are the alternatives to analytics platforms?**

Alternatives to analytics platforms can replace this type of software, either partially or completely:

[**Marketing analytics software**](https://www.g2.com/categories/marketing-analytics) **:** Businesses looking for tools geared toward marketing use cases and marketing data (e.g., related to targeting prospects) should look at marketing analytics solutions that are purpose-built for this.

[**Sales analytics software**](https://www.g2.com/categories/sales-analytics) **:** Although sales data such as revenue forecasts and closed deals can be imported and analyzed in general-purpose analytics platforms, sales analytics platforms can provide a more granular analysis of sales-related data and might have better integrations with sales tools such as CRMs. 

[**Log analysis software**](https://www.g2.com/categories/log-analysis) **:**  If a business wants to focus on analyzing its log data from applications and systems, it could benefit from log analysis software, which helps enable the documentation of application log files for records and analytics.

[**Predictive analytics software**](https://www.g2.com/categories/predictive-analytics) **:** Broad-purpose analytics platforms allow businesses to conduct various forms of analysis, such as prescriptive, descriptive, and predictive. Since analytics platforms allow for these different types of analyses, they might not provide the most robust features for any type. Therefore, businesses focused on looking at past and present data to predict future outcomes can use predictive analytics software for a more fine-tuned solution. 

[**Text analysis software**](https://www.g2.com/categories/text-analysis) **:** Analytics platforms are focused on structured or numerical data, allowing users to drill down and dig into numbers to inform business decisions. Text analysis solutions are the best bet if the user is looking to focus on unstructured or text data. These tools help users quickly understand and pull sentiment analysis, key phrases, themes, and other insights from unstructured text data.

[**Data visualization software**](https://www.g2.com/categories/data-visualization) **:** Data visualization tools can be an excellent place for businesses to start when looking to better understand their data. With capabilities including dashboards and reporting, data visualization software can often be quick and easy to set up and is frequently cheaper than more robust analytics platforms. 

However, it is essential to recognize their limitations. Data visualization solutions do what they say on the box: visualization. They do not give the user an end-to-end analytics solution from data preparation to data insights, nor do they provide significant data management capabilities.

### **Software and services related to analytics platforms**

Related solutions that can be used together with analytics platforms include:

[**Embedded business intelligence software**](https://www.g2.com/categories/embedded-business-intelligence) **:** Analytics platforms are standalone platforms that help companies analyze data. Businesses who want to build analytics capabilities into applications, whether that be for internal or external use, can use embedded BI software to accomplish this goal.

[**Database software**](https://www.g2.com/categories/database-software) **:** There are a plethora of solutions for storing, organizing, and sharing large amounts of data that can later be accessed and analyzed by analytics tools. Database software includes everything from [big data software](https://www.g2.com/categories/big-data) to traditional table-based [relational databases](https://www.g2.com/categories/relational-databases). Businesses should research and implement whichever database tools make the most sense for their particular data types or analytical needs. 

When considering an analytics solution, users should investigate which databases can integrate with the tool to make the most logical product choice for their situation. Analytics products would not serve much purpose without one or more company databases to pull data from when the time comes.

### Challenges with analytics platforms

**Configuration:** Analytics solutions may have a highly technical setup process, requiring IT or developmental expertise. When trying to implement one of these platforms without an in-house data scientist or IT professional, users may struggle with getting the technology off the ground, integrating it with the appropriate solutions, and creating queries for data collection. This could mean a significant loss of resources and an inability to use the tool as intended. Users can contact BI consulting providers for assistance setting up a program or, in some cases, for handling the entirety of BI reporting.

**Overreliance:** Focusing too much on data and analytics can also be problematic. Data-driven decisions are critical to a business’s success, but data-only decisions ignore the various voices from within and without the organization. Successful companies combine rigorous analytics with anecdotal storytelling and thoughtful conversations about the business's success and components.

**Integrations:** If the analytics tool does not fully integrate with existing software, getting a complete view of a business’s operational performance becomes challenging. Similarly, if an integration experiences a communication error or other issue during a data query, it causes an incorrect or incomplete reading. Users should make a point to monitor these connections and any potential performance issues throughout their software stack to ensure that correct, complete, and up-to-date information is being processed and displayed on dashboards.

**Data security:** Companies must consider security options to ensure the right users see the correct data and guarantee strict data security. Effective analytics solutions should offer security options that enable administrators to assign verified users different levels of access to the platform based on their security clearance or level of seniority.

### How to choose the best analytics tools

#### Requirements Gathering (RFI/RFP) for Analytics Platforms

If a company is just starting and looking to purchase the first analytics platform, or maybe an organization needs to update a legacy system--wherever a business is in its buying process, g2.com can help select the best analytics platform.

The particular business pain points might be related to all the manual work that must be completed. If the company has amassed a lot of data, it needs to look for a solution that can grow with the organization. Users should think about the pain points and jot them down; these should be used to help create a checklist of criteria. Additionally, the buyer must determine the number of employees needing this software, as this drives the number of licenses they will likely buy.

Taking a holistic overview of the business and identifying pain points can help the team springboard into creating a checklist of criteria. The checklist is a detailed guide with necessary and nice-to-have features, including budget, features, number of users, integrations, security requirements, cloud or on-premises solutions, and more.

Depending on the deployment scope, producing an RFI, a one-page list with a few bullet points describing what is needed from an analytics platform might be helpful.

#### Compare Analytics Platforms Products

**Create a long list**

From meeting the business functionality needs to implementation, vendor evaluations are essential to the software buying process. For ease of comparison, after all demos are complete, it helps to prepare a consistent list of questions regarding specific needs and concerns to ask each vendor.

**Create a short list**

From the long list of vendors, it is helpful to narrow the list of vendors and come up with a shorter list of contenders, preferably no more than three to five. With this list, businesses can produce a matrix to compare the features and pricing of the various solutions.

**Conduct demos**

To ensure the comparison is thoroughgoing, the user should demo each solution on the shortlist with the same use case and datasets. This will allow the business to evaluate like for like and see how each vendor stacks up against the competition. 

#### Selection of analytics platforms

**Choose a selection team**

Before getting started, creating a winning team that will work together throughout the process, from identifying pain points to implementation, is crucial. The software selection team should consist of organization members with the right interests, skills, and time to participate in this process. A good starting point is to aim for three to five people who fill roles such as the primary decision maker, project manager, process owner, system owner, or staffing subject matter expert, as well as a technical lead, IT administrator, or security administrator. The vendor selection team may be more minor in smaller companies, with fewer participants, multitasking, and taking on more responsibilities.

**Analyze the data**

As analytics platforms are all about the data, the user must ensure that the selection process is also data-driven. The selection team should compare notes and facts and figures that they noted during the process, such as time to insight, number of visualizations, and availability of advanced analytics capabilities.

**Negotiation**

Just because something is written on a company’s pricing page does not mean it is gospel (although some companies will not budge). It is imperative to open up a conversation regarding pricing and licensing. For example, the vendor may be willing to discount multiyear contracts or recommend the product to others.

**Final decision**

After this stage, and before going all in, it is recommended to roll out a test run or pilot program to test adoption with a small sample size of users. If the tool is well used and received, the buyer can be confident that the selection was correct. If not, it might be time to return to the drawing board.

### How much do analytics software platforms cost?

As mentioned above, analytics platforms come as both on-premises and cloud solutions. Pricing between the two might differ, with the former often coming with more upfront costs for setting up the infrastructure. 

As with any software, analytics platforms are frequently available in different tiers, with the more entry-level solutions costing less than the enterprise-scale ones. The former will often not have as many features and may have caps on usage. Vendors may have tiered pricing, in which the price is tailored to the users’ company size, the number of users, or both. This pricing strategy may come with some support, which might be unlimited or capped at a certain number of hours per billing cycle.

Once set up, analytics platforms, especially those deployed in the cloud, do not often require significant maintenance costs.

As these platforms often come with many additional features, businesses looking to maximize the value of their software can contract third-party consultants to help them derive insights from their data and get the most out of the software.

#### Return on Investment (ROI)

Businesses deploy analytics platforms to derive a return on investment (ROI). As they are looking to recoup the losses they spent on the software, it is critical to understand its costs. As mentioned above, analytics platforms are typically billed per user, sometimes tiered, depending on the company size. More users will generally translate into more licenses, which means more money.

Users must consider how much is spent and compare that to what is gained in terms of efficiency and revenue. Therefore, businesses can compare processes between pre- and post-deployment software to understand better how processes have been improved and how much time has been saved. They can even produce a case study (either for internal or external purposes) to demonstrate the gains they have seen from using an analytics tool.

### Implementation of analytics software solutions

**How are analytics software Implemented?**

Implementation differs drastically depending on the complexity and scale of the data. In organizations with vast amounts of data in disparate sources (e.g., applications, databases, etc.), it is often wise to utilize an external party, whether an implementation specialist from the vendor or a third-party consultancy. With vast experience under their belts, they can help businesses understand how to connect and consolidate their data sources and use the software efficiently and effectively.

**Who is responsible for analytics platform implementation?**

Properly deploying an analytics platform may require many people or teams. This is because, as mentioned, data can cut across teams and functions. As a result, one person or even one team rarely has a complete understanding of all of a company’s data assets. With a cross-functional team, a business can begin to piece together its data and begin the analytics journey, starting with proper data preparation and management.

### Emerging trends related to analytics platforms

**Increase data accessibility**

Business data is no longer locked up in silos. With analytics platforms, more users across a business can find, access, and analyze this data. In addition, [artificial intelligence (AI) tools](https://www.g2.com/categories/artificial-intelligence) such as [natural language processing (NLP) software](https://www.g2.com/categories/natural-language-processing-nlp) help make searching through and for data more accessible and powerful, providing more accurate results.

With the amount of data accessible to businesses today, it is a near necessity that they implement some type of analytics software to understand and act on that data better. Implementing analytics software has been a significant initiative for companies undergoing digital transformation, as these tools offer deeper visibility into an organization's data. Companies adopt these solutions to make sense of large datasets collected from various sources.

**Shift from on-premises to cloud**

The move from on-premises data analytics to the cloud has been underway for several years, with more and more businesses moving their data and data insights into the cloud. This is taking place for various reasons, such as time to insight. Moving away from on-premises infrastructure has helped many companies enable data work anywhere one has access to the cloud—anywhere with internet access. However, not all data users have the luxury of working in the cloud for several reasons, including data security and issues related to latency. In industries such as health care, strict regulations such as the [Health Insurance Portability and Accountability Act (HIPAA)](https://learn.g2.com/health-insurance-portability-and-accountability-act) require data to be secure. Although it is possible to ensure this security in the cloud, it can be more complicated.

**Conversational AI**

Historically, to query data within an analytics solution, users needed to master a query language like SQL. With the rise of conversational interfaces, users uncover the data and insights they seek using intuitive language. Intuitive methods of querying data enable a larger user base to access and make sense of company data.

**Machine learning**

AI is quickly becoming a promising feature of analytics solutions throughout the data journey, from ingestion to insights. From AI-powered data preparation to smart insights, in which the platform suggests visualizations to the end user, analytics platforms are quickly becoming more powerful. Machine learning is helping end users discover hidden insights, allowing them to make sense of data and understand what they are seeing.

### Analytics Platforms FAQs

#### **Which analytics platforms have an intuitive UI that non-technical users adopt without extensive training?**

I looked for analytics platforms that make it easy to find what you need also enable easy collaboration.

- [Microsoft Power BI](https://www.g2.com/products/microsoft-microsoft-power-bi/reviews) **:** Has a drag-and-drop chart building without SQL or code that makes it user-friendly. Users can connect Excel, SharePoint, and emails without technical help. 
- [Tableau](https://www.g2.com/products/tableau/reviews) **:** Users can create dashboards with limited use and no deep technical background. Onboarding is as simple as sharing the links and giving the right access.
- [Sigma](https://www.g2.com/products/sigma-computing-sigma/reviews) **:** Spreadsheet-like UI provides the most distinctive non-technical adoption story. Users can pull in data and work with it in complicated ways that don't require coding.
- [Kyvos Semantic Layer](https://www.g2.com/products/kyvos-semantic-layer/reviews) **:** The semantic layer approach means business users interact with pre-defined, plain-language metrics rather than raw tables or SQL, which is the foundational mechanism for non-technical adoption. 

#### **What are the best analytics platforms for business teams accessing insights without SQL or data science skills?**

SQL-free access means business users can explore, filter, and create their own views without analyst dependency. 

- [Microsoft Power BI](https://www.g2.com/products/microsoft-microsoft-power-bi/reviews) **:** Non-technical users can build powerful dashboards quickly without SQL. Power BI's Power Query Editor handles data transformations through button clicks. The DAX layer exists for advanced users but is not required for standard self-service reporting.
- [Sigma](https://www.g2.com/products/sigma-computing-sigma/reviews) **:** Sigma's specific differentiator for SQL-free access is its spreadsheet-like interface on live warehouse data. For teams already on Snowflake or cloud warehouses, Sigma eliminates the SQL barrier entirely at the analysis layer.
- [Domo](https://www.g2.com/products/domo/reviews) **:** The no-code platform is easy to use for non-technical teams. Users can apply filtering and date range changes without any coding. The 1000+ connector ecosystem means data arrives automatically, so business users interact with dashboards rather than queries. 
- [Kyvos Semantic Layer](https://www.g2.com/products/kyvos-semantic-layer/reviews) **:** The semantic model defines metrics in plain language; business users query pre-built dimensions and measures without writing a single line of SQL. 

#### **Which analytics platforms support collaborative dashboards, annotations, and mobile access for on-the-go insights?**

I looked for tools with collaborative analytics, shared dashboards, in-platform discussion, annotations, and mobile-ready access.

- [Domo](https://www.g2.com/products/domo/reviews) **:** Sales teams can access data and contacts in real-time on their phones. Has platform-native discussion, report sharing, and insight annotation as part of the daily workflow. 
- [Microsoft Power BI](https://www.g2.com/products/microsoft-microsoft-power-bi/reviews) **:** Web and mobile access are daily-use features. The platform enables collaboration so everyone can see the same report at the same time, updated in real time.
- [Yellowfin BI](https://www.g2.com/products/yellowfin-bi/reviews) **:** Designed around collaborative BI with built-in story, annotation, and broadcast features for sharing insights with business audiences. 
- [Looker](https://www.g2.com/products/looker/reviews) **:** Comes with scheduled report delivery, so automated weekly numbers land in inboxes without anyone manually running anything. Email reports and metric notifications can be set up as daily workflow features. 

#### **Which analytics solutions provide fast query response and drill-down capability for ad-hoc exploration?**

Fast ad-hoc exploration means users can drill down, pivot, and filter without waiting and without writing a new query every time.

- [Tableau](https://www.g2.com/products/tableau/reviews) **:** Users can drill down on data without writing queries. Extracted datasets perform significantly better for ad-hoc work.
- [Kyvos Semantic Layer](https://www.g2.com/products/kyvos-semantic-layer/reviews) **:** The semantic layer pre-aggregates at the warehouse layer so ad-hoc queries against massive datasets return fast without full table scans. 
- [Incorta](https://www.g2.com/products/incorta/reviews) **:** Its direct data mapping approach eliminates the aggregation layer that slows most BI platforms during ad-hoc queries. For organizations where query latency on complex, multi-source datasets is the primary pain, Incorta is a good choice.
- [Microsoft Power BI](https://www.g2.com/products/microsoft-microsoft-power-bi/reviews) **:** Provides intuitive filtering across countries, teams, and time periods within existing dashboards without analyst involvement. The Direct Lake connection mode specifically reduces ad-hoc query latency.

#### **Which analytics solutions integrate with Snowflake, BigQuery, and Redshift seamlessly?**

Native, live connections to modern data warehouses — where queries run in the warehouse rather than in the BI tool are what seamless integration actually means for data teams.

- [Microsoft Power BI](https://www.g2.com/products/microsoft-microsoft-power-bi/reviews) **:** Integration with Active Directory, SharePoint, and the Microsoft Fabric ecosystem is described as genuinely seamless for organizations already in the Microsoft stack.
- [Sigma](https://www.g2.com/products/sigma-computing-sigma/reviews) **:** Built to run directly on Snowflake (and BigQuery/Redshift) without extracting data. The architecture means live warehouse queries are the default mode, not an optional feature.
- [Databricks](https://www.g2.com/products/databricks/reviews) **:** It is the warehouse-layer itself for many organizations, not a BI tool connecting to a warehouse, which means integration is inherently native. For organizations that treat Databricks as the processing layer and BI tools as the visualization layer on top, Databricks' own analytics features (via SQL Warehouses and notebooks) eliminate the need for a separate integration layer.
- [Looker](https://www.g2.com/products/looker/reviews) **:** BigQuery is the most-named data warehouse in Looker's review base. LookML's push-down SQL architecture means all queries run in the warehouse (Snowflake, BigQuery, Redshift) rather than being extracted into Looker.

#### **Which analytics solutions come with robust caching and performance optimization to maintain fast speeds at scale?**

Caching and performance optimization matter when datasets are large, dashboards are complex, and business users can't wait for queries to resolve.

- [Kyvos Semantic Layer](https://www.g2.com/products/kyvos-semantic-layer/reviews) **:** The semantic layer pre-aggregates at the warehouse layer specifically to make large dataset queries fast. For organizations where query latency on multi-billion row datasets is the blocking problem, Kyvos is the most purpose-built and best-validated option in the category on these dimensions.
- [Databricks](https://www.g2.com/products/databricks/reviews) **:** Photon engine, Delta Lake caching, and auto-scaling compute architecture are the performance mechanisms at scale. 
- [Microsoft Power BI](https://www.g2.com/products/microsoft-microsoft-power-bi/reviews) **:** Row Level Security, Premium capacity, and aggregation tables are the scale optimization toolkit. Performance at scale in Power BI is achievable but requires deliberate architecture, not automatic.
- [Incorta](https://www.g2.com/products/incorta/reviews) **:** Direct data mapping eliminates the pre-aggregation step that creates scale bottlenecks in most BI tools, allowing ad-hoc queries against large transactional datasets to run without a separate aggregation cache. 

#### **Which analytics platforms prevent incorrect conclusions by enforcing data governance and preventing metric manipulation?**

I looked for analytics platforms with strong data governance features. 

- [Looker](https://www.g2.com/products/looker/reviews) **:** LookML governance, real-time data access, and seamless integration with modern data warehouses together create the governed analytics environment enterprises need to prevent metric drift across teams.
- [Microsoft Power BI](https://www.g2.com/products/microsoft-microsoft-power-bi/reviews) **:** Addresses governance through Row Level Security, workspace permissions, and certified datasets, which restrict what data individual users can see and prevent unauthorized metric redefinition.
- [Kyvos Semantic Layer](https://www.g2.com/products/kyvos-semantic-layer/reviews) **:** It defines metrics once at the semantic model level and enforces those definitions for every downstream query and dashboard. 
- [Tableau](https://www.g2.com/products/tableau/reviews) **:** Governance approach is built around Tableau Server and Tableau Cloud — where published data sources become the certified metric layer that individual report builders consume rather than create.