# Best Big Data Analytics Software - Page 3 ## How Many Big Data Analytics Software Products Does G2 Track? **Total Products under this Category:** 110 ### Category Stats (Aug 2026) - **Average Rating:** 4.46/5 The average rating of products in this category, based on all submitted ratings - **Top Trending Product:** Datacoves (+0.27%) - Among all products in this category, Datacoves recorded the largest rating increase compared to last month _Last updated: August 01, 2026_ ## How Does G2 Rank Big Data Analytics Software Products? **Why You Can Trust G2's Software Rankings:** - 30 Analysts and Data Experts - 8,400+ Authentic Reviews - 110+ 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 Big Data Analytics Software ![G2 Grid® for Big Data Analytics Software plotting products by satisfaction and market presence](https://www.g2.com/categories/big-data-analytics/grids.png?focus%5B%5D=10470&focus%5B%5D=6073&focus%5B%5D=10938&focus%5B%5D=1308796&focus%5B%5D=989&focus%5B%5D=67962&focus%5B%5D=27024&focus%5B%5D=52199) Highlighted products: Databricks, Google Cloud BigQuery, Snowflake, IBM watsonx.data, Alteryx, Azure Databricks, Kyvos Semantic Layer, and Azure Synapse Analytics. Underlying data: [Grid® JSON](https://www.g2.com/categories/big-data-analytics/grids.json?focus%5B%5D=databricks&focus%5B%5D=google-cloud-bigquery&focus%5B%5D=snowflake&focus%5B%5D=ibm-watsonx-data&focus%5B%5D=alteryx&focus%5B%5D=azure-databricks&focus%5B%5D=kyvos-semantic-layer&focus%5B%5D=azure-synapse-analytics) **Sponsored** ### Alteryx Alteryx, through it's Alteryx One platform, helps enterprises transform complex, disconnected data into a clean, AI-ready state. Whether you’re creating financial forecasts, analyzing supplier performance, segmenting customer data, analyzing employee retention, or building competitive AI applications from your proprietary data, Alteryx One makes it easy to cleanse, blend, and analyze data to unlock the unique insights that drive impactful decisions. AI-Guided Analytics Alteryx automates and simplifies every stage of data preparation and analysis, from validation and enrichment to predictive analytics and automated insights. Incorporate generative AI directly into your workflows to streamline complex data tasks and generate insights faster. Unmatched flexibility, whether you prefer code-free workflows, natural language commands, or low-code options, Alteryx adapts to your needs. Trusted. Secure. Enterprise-Ready. Alteryx is trusted by over half of the Global 2000 and 19 of the top 20 global banks. With built-in automation, governance, and security, your workflows can scale and maintain compliance while delivering consistent results. And it doesn’t matter if your systems are on-premises, hybrid, or in the cloud; Alteryx fits effortlessly into your infrastructure. Easy to Use. Deeply Connected. What truly sets Alteryx apart is our focus on efficiency and ease of use for analysts and our active community of 700,000 Alteryx users to support you at every step of your journey. With seamless integration to data everywhere including platforms like Databricks, Snowflake, AWS, Google, SAP, and Salesforce, our platform helps unify siloed data and accelerate getting to insights. Visit Alteryx.com for more information, and to start your free trial. [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=1041&secure%5Bchosen_at%5D=2026-08-02T16%3A33%3A21Z&secure%5Bdisplayable_resource_id%5D=1041&secure%5Bdisplayable_resource_type%5D=Category&secure%5Bmedium%5D=sponsored&secure%5Bplacement_reason%5D=page_category&secure%5Bplacement_resource_ids%5D%5B%5D=1041&secure%5Bprioritized%5D=false&secure%5Bproduct_id%5D=989&secure%5Bresource_id%5D=1041&secure%5Bresource_type%5D=Category&secure%5Bsource_type%5D=category_page&secure%5Bsource_url%5D=https%3A%2F%2Fwww.g2.com%2Fcategories%2Fbig-data-analytics%3Fpage%3D3%26scid%3DIt-JG6svAa&secure%5Btoken%5D=5c901ec534f1c07273c2ac8441a4a38c5ff7e8e75ba586d7e0d216b11d19c10f&secure%5Burl%5D=https%3A%2F%2Fwww.alteryx.com%2Ftrial%3Futm_source%3Dg2%26utm_medium%3Dreviewsite%26utm_campaign%3DFY25_Global_AllRegions_AlwaysOn_AllPersonas_IndustryAgnostic%26utm_content%3Dg2_freetrial&secure%5Burl_type%5D=free_trial) ### [Keboola](https://www.g2.com/products/keboola/reviews) Keboola is a finance data and AI platform for companies that need trusted financial reporting, planning, analysis, and close processes across complex systems. Built for CFOs, FP&A teams, Controllers, finance operations, and data teams, Keboola helps organizations turn fragmented data from ERPs, accounting systems, spreadsheets, CRM, warehouses, and operational tools into one governed foundation for financial intelligence. Many finance teams rely on disconnected systems, inconsistent charts of accounts, manual reconciliations, and spreadsheet-based reporting. This makes it difficult to close quickly, produce reliable forecasts, answer board questions, support acquisitions, or use AI safely with financial data. Keboola solves this upstream data problem by connecting, standardizing, transforming, and governing financial data before it reaches FP&A, CPM, BI, reporting, or AI tools. Keboola is especially valuable for multi-entity companies, private-equity-backed businesses, holding groups, financial services firms, franchises, and organizations growing through M&A. These companies often operate across multiple ERPs, entities, countries, currencies, and reporting definitions. Keboola helps standardize chart-of-accounts logic, automate financial data pipelines, reconcile data across systems, and create trusted business definitions that teams can use consistently. Unlike traditional FP&A, CPM, EPM, budgeting, forecasting, or financial reporting tools that assume clean data already exists, Keboola focuses on the governed data foundation underneath. The platform gives teams transparent, auditable logic for financial transformations, source-to-output lineage, reusable business rules, and a semantic layer that helps ensure reports, dashboards, forecasts, and AI outputs are based on trusted company data. Keboola works alongside existing tools such as Snowflake, BigQuery, Databricks, Microsoft Fabric, Power BI, Tableau, Looker, Anaplan, Pigment, DataRails, Workiva, and other finance and analytics platforms. Rather than forcing a rip-and-replace project, Keboola strengthens the data layer beneath these systems so finance teams can plan, report, reconcile, and analyze with greater confidence. For AI adoption, Keboola provides the governed data environment that makes AI practical for business-critical financial workflows. Teams can connect AI agents and assistants to approved metrics, trusted pipelines, financial definitions, and auditable data products, reducing the risk of confident but untraceable answers. With Keboola, organizations can improve financial analysis, accelerate reporting, support financial close, automate reconciliation workflows, enable more reliable FP&A, and create a trusted foundation for AI-powered finance. **Average Rating:** 4.6/5.0 **Total Reviews:** 138 #### How Do G2 Users Rate Keboola? - **Has the product been a good partner in doing business?:** 9.0/10 (Category avg: 8.9/10) - **Multi-Source Analysis:** 8.3/10 (Category avg: 8.5/10) - **Real-Time Analytics:** 5.0/10 (Category avg: 8.5/10) - **Data Workflow:** 9.2/10 (Category avg: 8.5/10) #### Who Is the Company Behind Keboola? - **Seller:** [Keboola](https://www.g2.com/sellers/keboola) - **Year Founded:** 2008 - **HQ Location:** Prague - **Twitter:** @keboola 2,004 Twitter followers - **LinkedIn® Page:** [www.linkedin.com](https://www.g2.com/external_clickthroughs/record?secure%5Bsource_type%5D=product_profile&secure%5Btoken%5D=ef5c258c3c12e985009d017bdcea8d30cdde56e2d89dcd2f873f739b37335044&secure%5Burl%5D=https%3A%2F%2Fwww.linkedin.com%2Fcompany%2Fkeboola%2F&secure%5Burl_type%5D=linkedin_company_website) 97 employees on LinkedIn® #### Who Uses This Product? - **Who Uses This:** Data Analyst, Data Engineer - **Top Industries:** Information Technology and Services, Marketing and Advertising - **Company Size:** 63% Medium, 22% Small #### What Do G2 Reviewers Say About Keboola? _AI-generated summary from verified user reviews_ ##### Pros - Users find Keboola's platform to be **simple and easy to use** , making data management accessible for everyone. - Users value the **user-friendly data management** capabilities of Keboola, enhancing accessibility for non-technical individuals. - Users praise the **intuitive setup for data flows** in Keboola, enhancing productivity with seamless data handling. - Users value the **extensive integrations** of Keboola, enabling seamless data management across various platforms and tools. - Users praise Keboola for its **incredible customer support** , providing fast and helpful assistance to enhance their experience. ##### Cons - Users find the **learning curve steep** , often requiring developer assistance and causing confusion with component navigation. - Users struggle with the **complexity** of Keboola, facing steep learning curves and inconsistent documentation that hinders usability. - Users face a **steep learning curve** with Keboola, often needing external help to navigate its complexities effectively. - Users find the **interface difficult to navigate** , making data management more complex and error-prone than expected. - Users find the **user interface overwhelming** and not intuitive, resulting in a challenging learning experience for newcomers. #### What Are Recent G2 Reviews of Keboola? **["Usefull tool with good people behind it"](https://www.g2.com/survey_responses/keboola-review-13121874)** **Rating:** 4.5/5.0 stars _— Verified User in Wholesale_ [Read full review](https://www.g2.com/survey_responses/keboola-review-13121874) **["Keboola’s Intuitive UI Makes Big-Data Pipelines and Transformations Effortless"](https://www.g2.com/survey_responses/keboola-review-13168406)** **Rating:** 4.5/5.0 stars _— Verified User in Logistics and Supply Chain_ [Read full review](https://www.g2.com/survey_responses/keboola-review-13168406) #### What Are G2 Users Discussing About Keboola? - [What are the benefits and challenges of using Keboola for data integration, and what do you recommend for new users?](https://www.g2.com/discussions/what-are-the-benefits-and-challenges-of-using-keboola-for-data-integration-and-what-do-you-recommend-for-new-users) ### [Plotly Dash Enterprise](https://www.g2.com/products/plotly-dash-enterprise/reviews) Dash is the trusted solution for operationalizing Python models, allowing data science teams to focus on data and models, while still producing and deploying enterprise-ready apps. What would typically require a team of back-end developers, front-end developers and IT can all be done with Dash. It enables data science teams to build, design, deploy, and securely manage data-driven applications that align with your business goals. Companies can deliver on their data, analytic, and AI initiatives quickly and effectively -- no JavaScript, CSS, CronJobs or DevOps required. **Average Rating:** 4.8/5.0 **Total Reviews:** 36 #### How Do G2 Users Rate Plotly Dash Enterprise? - **Has the product been a good partner in doing business?:** 8.8/10 (Category avg: 8.9/10) #### Who Is the Company Behind Plotly Dash Enterprise? - **Seller:** [Plotly](https://www.g2.com/sellers/plotly) - **Year Founded:** 2013 - **HQ Location:** Montréal, CA - **Twitter:** @plotlygraphs 41,308 Twitter followers - **LinkedIn® Page:** [www.linkedin.com](https://www.g2.com/external_clickthroughs/record?secure%5Bsource_type%5D=product_profile&secure%5Btoken%5D=333261e482ab8eeda91d8b94f8944150fd0b5c49c67c2f514107b3eda84f9046&secure%5Burl%5D=https%3A%2F%2Fwww.linkedin.com%2Fcompany%2F3327684%2F&secure%5Burl_type%5D=linkedin_company_website) 105 employees on LinkedIn® #### Who Uses This Product? - **Top Industries:** Computer Software - **Company Size:** 47% Small, 31% Large #### What Do G2 Reviewers Say About Plotly Dash Enterprise? _AI-generated summary from verified user reviews_ ##### Pros - Users love the **ease of creating beautiful visualizations** with Drag-and-Drop features in Plotly Dash Enterprise. - Users love the **coding ease** of Plotly Dash Enterprise, allowing simple chart creation through drag and drop functionality. - Users value the **customer support** of Plotly Dash Enterprise, enhancing their experience with prompt and effective assistance. - Users love the **intuitive dashboard management** of Plotly Dash Enterprise, enhancing efficiency with easy visualizations and SQL support. - Users value the **ease of creating stunning visualizations** in Plotly Dash Enterprise, enhancing their data presentation experience. #### What Are Recent G2 Reviews of Plotly Dash Enterprise? **["Its the perfect Data Management"](https://www.g2.com/survey_responses/plotly-dash-enterprise-review-10698270)** **Rating:** 4.5/5.0 stars _— Maria F._ [Read full review](https://www.g2.com/survey_responses/plotly-dash-enterprise-review-10698270) **["Dash Dominance in Creating Interactive Web Apps for Your Data Insights"](https://www.g2.com/survey_responses/plotly-dash-enterprise-review-8889756)** **Rating:** 5.0/5.0 stars _— Uttam M._ [Read full review](https://www.g2.com/survey_responses/plotly-dash-enterprise-review-8889756) #### What Are G2 Users Discussing About Plotly Dash Enterprise? - [What are 3 benefits of a dashboard?](https://www.g2.com/discussions/dash-what-are-3-benefits-of-a-dashboard) - [What is the best dashboard software?](https://www.g2.com/discussions/dash-what-is-the-best-dashboard-software) - [How good is Dash?](https://www.g2.com/discussions/how-good-is-dash) - [What is the function of a dashboard?](https://www.g2.com/discussions/what-is-the-function-of-a-dashboard) ### [Strategy Mosaic](https://www.g2.com/products/strategy-mosaic/reviews) Strategy Mosaic, from Strategy (formerly MicroStrategy), is an enterprise-grade universal semantic layer solution designed to enhance the capabilities of AI and Business Intelligence (BI) within organizations. It addresses critical challenges such as data fragmentation and inconsistent metrics, which lead to untrusted AI answers, compliance risks, and runaway cloud costs. The universal semantic layer that Mosaic provides serves as a centralized repository for business definitions, hierarchies, and security rules, ensuring that all users access consistent metrics and KPIs regardless of the tools they employ. This single source of truth is actively monitored by our integrated Sentinel layer, which moves you from reactive audits to proactive, real-time governance. Sentinel provides immediate intelligence on potential data breaches, compliance risks, and cost-saving opportunities, helping you optimize cloud spend and prevent violations before they happen. Additionally, Mosaic empowers organizations to build an auditable foundation for AI. By providing a layer of rich business context and consistent, human-readable definitions, Mosaic gives AI models the deep understanding required to provide more accurate and verifiable answers. This accelerates time to insight, allows you to end vendor lock-in, and dramatically reduces the total cost of ownership (TCO) by eliminating costly data rework and optimizing data management processes. In summary, Strategy Mosaic stands out by addressing the fundamental issues of data fragmentation and governance. Its robust connectivity, centralized semantic layer, and focus on delivering trusted data make it an invaluable tool for organizations aiming to enhance their analytics capabilities and leverage AI effectively. **Average Rating:** 4.5/5.0 **Total Reviews:** 15 #### How Do G2 Users Rate Strategy Mosaic? - **Has the product been a good partner in doing business?:** 9.1/10 (Category avg: 8.9/10) - **Multi-Source Analysis:** 8.3/10 (Category avg: 8.5/10) - **Real-Time Analytics:** 9.2/10 (Category avg: 8.5/10) - **Data Workflow:** 10.0/10 (Category avg: 8.5/10) #### Who Is the Company Behind Strategy Mosaic? - **Seller:** [Strategy (formerly MicroStrategy)](https://www.g2.com/sellers/strategy-formerly-microstrategy) - **Company Website:** www.strategy.com - **Year Founded:** 1989 - **HQ Location:** Tysons Corner, VA - **Twitter:** @MicroStrategy 303,456 Twitter followers - **LinkedIn® Page:** [www.linkedin.com](https://www.g2.com/external_clickthroughs/record?secure%5Bsource_type%5D=product_profile&secure%5Btoken%5D=8f32382ee6ea0cc02d6dc7c1fe37038f1247aceba92d8d5030350f4ffb1e6c92&secure%5Burl%5D=https%3A%2F%2Fwww.linkedin.com%2Fcompany%2Fstrategy%2F&secure%5Burl_type%5D=linkedin_company_website) 3,457 employees on LinkedIn® #### Who Uses This Product? - **Company Size:** 53% Large, 40% Medium #### What Do G2 Reviewers Say About Strategy Mosaic? _AI-generated summary from verified user reviews_ ##### Pros - Users appreciate the **ease of use** in Strategy Mosaic, simplifying collaboration and enhancing clarity in planning and execution. - Users value the **structured planning and AI-assisted metrics creation** of Strategy Mosaic, enhancing collaboration and clarity. - Users value the **reliable and user-friendly reporting** features of Strategy Mosaic, appreciating its robust semantic layer. - Users value the **robust data analysis** capabilities of Strategy Mosaic, ensuring reliable insights from vast data volumes. - Users enjoy the **auto-magical experience** of quickly creating their initial data model with Strategy Mosaic. ##### Cons - Users experience **minor bugs** with Strategy Mosaic, particularly affecting cube publishing and code corrections. - Users report encountering **bug issues** that persist even after attempting to correct errors in Strategy Mosaic. - Users experience **debugging issues** with Strategy Mosaic, as corrections do not reflect in the code as expected. - Users note the **high licensing costs** of Strategy Mosaic and suggest exploring more affordable options for better value. - Users find the **initial learning curve** of Strategy Mosaic challenging, making the platform feel overwhelming for newcomers. #### What Are Recent G2 Reviews of Strategy Mosaic? **["Strategy Mosaic Makes Strategic Planning Clear, Visual, and Team-Aligned"](https://www.g2.com/survey_responses/strategy-mosaic-review-12611240)** **Rating:** 4.0/5.0 stars _— Akash A._ [Read full review](https://www.g2.com/survey_responses/strategy-mosaic-review-12611240) **["Effortless Planning and Team Alignment Made Simple"](https://www.g2.com/survey_responses/strategy-mosaic-review-12008071)** **Rating:** 4.5/5.0 stars _— Aditya K._ [Read full review](https://www.g2.com/survey_responses/strategy-mosaic-review-12008071) ### [Datacoves](https://www.g2.com/products/datacoves/reviews) Datacoves is an enterprise DataOps platform with managed dbt Core and Airflow for data transformation and orchestration. We offer VS Code in the browser for dbt development with the ability to include preferred VS Code extensions and Python libraries such as the official Snowflake Extension and Snowpark. You may also optionally use our managed Airbyte and Superset for a full end-to-end solution. **Average Rating:** 4.8/5.0 **Total Reviews:** 19 #### How Do G2 Users Rate Datacoves? - **Has the product been a good partner in doing business?:** 9.6/10 (Category avg: 8.9/10) - **Multi-Source Analysis:** 9.3/10 (Category avg: 8.5/10) - **Real-Time Analytics:** 8.3/10 (Category avg: 8.5/10) - **Data Workflow:** 8.9/10 (Category avg: 8.5/10) #### Who Is the Company Behind Datacoves? - **Seller:** [Datacoves Inc](https://www.g2.com/sellers/datacoves-inc) - **Year Founded:** 2021 - **HQ Location:** Thousand Oaks, California - **Twitter:** @datacoves 475 Twitter followers - **LinkedIn® Page:** [www.linkedin.com](https://www.g2.com/external_clickthroughs/record?secure%5Bsource_type%5D=product_profile&secure%5Btoken%5D=0d506e3247033352dea4ac380cfe05a1fd6ac756b6f5cb9a2596c999b5a2aa91&secure%5Burl%5D=https%3A%2F%2Fwww.linkedin.com%2Fcompany%2Fdatacoves%2F&secure%5Burl_type%5D=linkedin_company_website) 12 employees on LinkedIn® #### Who Uses This Product? - **Company Size:** 47% Large, 26% Medium #### What Do G2 Reviewers Say About Datacoves? _AI-generated summary from verified user reviews_ ##### Pros - Users highlight the **ease of use** of Datacoves, praising its straightforward setup and supportive implementation process. - Users appreciate the **well-thought-out development process** of Datacoves, which enhances productivity and teamwork in data engineering. - Users value the **seamless integrations** of Datacoves, enhancing collaboration and simplifying complex data workflows effectively. - Users appreciate the **best-in-breed data engineering tools** of Datacoves, enhancing collaboration and improving data quality effectively. - Users appreciate the **easy integrations** of Datacoves, streamlining collaboration and improving overall data pipeline efficiency. ##### Cons - Users feel the **alert overload** can lead to confusion and strain on customer support during service failures. - Users find the **lack of dashboard integrations** limits their ability to monitor activity and manage resources effectively. - Users express concerns about **being locked into specific ELT tools** , which may limit flexibility for some. - Some users feel **locked into their ELT tools** , which may limit flexibility and cause frustration. - Users note the **difficult learning** curve due to the need for extensive customization with Datacoves. #### What Are Recent G2 Reviews of Datacoves? **["Great Developer Experience with Responsive Support"](https://www.g2.com/survey_responses/datacoves-review-12882735)** **Rating:** 5.0/5.0 stars _— Anthony L._ [Read full review](https://www.g2.com/survey_responses/datacoves-review-12882735) **["Datacoves Delivers Stable, Managed Airflow with Seamless dbt + Snowflake Integration"](https://www.g2.com/survey_responses/datacoves-review-13115559)** **Rating:** 5.0/5.0 stars _— Alex S._ [Read full review](https://www.g2.com/survey_responses/datacoves-review-13115559) ### [Megaladata](https://www.g2.com/products/megaladata/reviews) The low code Megaladata platform empowers business users by making advanced analytics accessible. - Visual design of complex data analysis models with no involvement of the IT department and no need for programming. - Over 60 ready-to-use processing components. - Easy integration with various sources. - Fast processing of large datasets achieved through in-memory computing and parallelism. - Reusable components that facilitate accumulation of business expertise. - Advanced visualization — OLAP cubes, tables, charts, and other specialized tools. Megaladata minimizes the time between hypothesis testing and a fully functional business process. **Average Rating:** 4.9/5.0 **Total Reviews:** 8 #### How Do G2 Users Rate Megaladata? - **Multi-Source Analysis:** 10.0/10 (Category avg: 8.5/10) - **Data Workflow:** 10.0/10 (Category avg: 8.5/10) #### Who Is the Company Behind Megaladata? - **Seller:** [Megaladata](https://www.g2.com/sellers/megaladata) - **HQ Location:** Neu-Isenburg, DE - **Twitter:** @megaladata\_com 5 Twitter followers - **LinkedIn® Page:** [www.linkedin.com](https://www.g2.com/external_clickthroughs/record?secure%5Bsource_type%5D=product_profile&secure%5Btoken%5D=061b6364dee02e318c6fe6a8a981f8186c4715e88c17473ba2dbf3c2024fa4de&secure%5Burl%5D=https%3A%2F%2Fwww.linkedin.com%2Fcompany%2Fmegaladata&secure%5Burl_type%5D=linkedin_company_website) 5 employees on LinkedIn® #### Who Uses This Product? - **Company Size:** 88% Small, 13% Medium #### What Are Recent G2 Reviews of Megaladata? **["Reusable Components and Nice Performance"](https://www.g2.com/survey_responses/megaladata-review-12780960)** **Rating:** 5.0/5.0 stars _— Vitali M._ [Read full review](https://www.g2.com/survey_responses/megaladata-review-12780960) **["Megaladata is a platform for any time of on-time analytics"](https://www.g2.com/survey_responses/megaladata-review-12752778)** **Rating:** 5.0/5.0 stars _— Vartan G._ [Read full review](https://www.g2.com/survey_responses/megaladata-review-12752778) ### [Savant Labs](https://www.g2.com/products/savant-labs/reviews) Savant is an AI workflow automation platform built for enterprise finance, tax, and accounting teams. It turns messy, manual data work like extraction, preparation, reconciliation, and reporting into centrally governed, audit-ready workflows, driving efficiency without sacrificing accuracy, control, or compliance. Savant integrates with your preferred LLM, including Claude, Copilot, ChatGPT, and private LLMs, so you control model choice, data residency, and cost. Ask in plain language for the workflow you want to build, or simply say "run this month's reconciliation," and Savant turns that instruction into a repeatable, governed, auditable workflow. Trusted by Fortune 500 enterprises, Savant catches errors before they're filed, ensures audit readiness without the scramble, and gives finance teams their time back. WHAT SETS SAVANT APART Unlike general-purpose AI tools or legacy analytics platforms, Savant was built specifically for finance workflows where 99% accuracy isn't good enough — because 1% errors at scale become audit findings, restatements, and compliance exposure. Three things make Savant different - Deterministic, not probabilistic: Savant uses rule-based AI agents, not LLM guesses. Consistent inputs produce consistent outputs. - Governance and auditability are built in, not bolted on: Audit trail, data lineage, SOX controls, role-based access, and evidence packs are standard, not add-ons. - Handles the data other tools can't: Native processing for PDFs, scanned documents, and invoices — the unstructured data that breaks legacy workflows. KEY FEATURES - AI-powered workflow automation: Automate any workflow end to end — financial reconciliation, month-end close, tax provisioning, accruals, and more. Works with structured and unstructured data, including PDFs, scanned documents, and ERP extracts. - Reproducible results: AI agents follow step-by-step logic with validation at each stage. Same inputs produce the same outputs, every time — no black boxes, no probabilistic guesses. - Built-in audit trail, data lineage, and evidence packs: Every workflow step is logged automatically. Complete data lineage from source to output. No manual documentation, no reconstructing steps across email chains. - SOX compliance by design: Segregation of duties, version control, approval management, and user activity history are built in from day one. - Human-in-the-loop exception handling: Savant proactively flags exceptions for human review, allowing analysts to catch errors before they reach a filing. The AI learns from human judgments over time. - 500+ enterprise connectors: Connect to your existing ERPs, CRMs, BI platforms, file systems, email, and more out of the box. - Enterprise-grade security: SOC 2 Type II, SOC 1 Type II, ISO 27001. SSO/SAML, role-based access control, private cloud and VPC deployment available. USE CASES - Month-end and year-end close automation - Financial reconciliations and tie-outs - Tax provision preparation - State apportionment calculations - Sales and use tax reconciliation - Data extraction from PDFs, invoices, and scanned documents - ERP data consolidation across multiple systems - Intercompany accounting and multi-entity reporting - Audit evidence package preparation - Recurring reporting and dashboard publishing **Average Rating:** 4.7/5.0 **Total Reviews:** 49 #### How Do G2 Users Rate Savant Labs? - **Has the product been a good partner in doing business?:** 9.8/10 (Category avg: 8.9/10) - **Multi-Source Analysis:** 9.2/10 (Category avg: 8.5/10) - **Real-Time Analytics:** 9.2/10 (Category avg: 8.5/10) - **Data Workflow:** 9.2/10 (Category avg: 8.5/10) #### Who Is the Company Behind Savant Labs? - **Seller:** [Savant Labs](https://www.g2.com/sellers/savant-labs) - **Company Website:** www.savantlabs.io - **Year Founded:** 2021 - **HQ Location:** San Francisco, California - **LinkedIn® Page:** [www.linkedin.com](https://www.g2.com/external_clickthroughs/record?secure%5Bsource_type%5D=product_profile&secure%5Btoken%5D=5dcb585c5245667215a14c13aa5332e041e2aa08dcb405a69812a52bc310dd41&secure%5Burl%5D=https%3A%2F%2Fwww.linkedin.com%2Fcompany%2Fsavant-labs&secure%5Burl_type%5D=linkedin_company_website) 61 employees on LinkedIn® #### Who Uses This Product? - **Top Industries:** Computer Software, Logistics and Supply Chain - **Company Size:** 44% Large, 40% Medium #### What Do G2 Reviewers Say About Savant Labs? _AI-generated summary from verified user reviews_ ##### Pros - Users appreciate the **ease of use** of Savant Labs, enjoying its intuitive interface and seamless analytics capabilities. - Users appreciate the **friendly and responsive customer support** that effectively addresses issues and inquiries promptly. - Users love the **user-friendly interface** , which simplifies analytics and enhances productivity with seamless data integration. - Users appreciate the **easy integrations** with Google Drive and other tools, enhancing analysis efficiency without coding. - Users love the **easy integrations** with various data sources, enhancing their analytics experience without coding knowledge. ##### Cons - Users note a **steep learning curve** with Savant Labs, requiring practice and patience to navigate effectively. - Users find the **learning difficulty** with Savant Labs steep, requiring practice to navigate its innovative features effectively. - Users experience **integration issues** with Savant Labs, facing difficulties in updating data sources and tool functionality. - Users face significant **access issues** , particularly with personal email logins and outdated tools during analyses. - Users face challenges with **data management** , particularly in updating sources and refreshing analyses effectively. #### What Are Recent G2 Reviews of Savant Labs? **["Faster close + auditors actually trust our process now"](https://www.g2.com/survey_responses/savant-labs-review-12941283)** **Rating:** 5.0/5.0 stars _— Lawrence M._ [Read full review](https://www.g2.com/survey_responses/savant-labs-review-12941283) **["Automated sales tax reconciliation and significantly shortened month-end close"](https://www.g2.com/survey_responses/savant-labs-review-12942104)** **Rating:** 5.0/5.0 stars _— Marlene S._ [Read full review](https://www.g2.com/survey_responses/savant-labs-review-12942104) ### [Deep.BI](https://www.g2.com/products/deep-bi/reviews) Deep.BI measures content consumption metrics and provides user engagement scoring to power publisher's content delivery, marketing tools and paywalls to grow, engage and retain audiences. Deep.BI collects all kinds of raw event data related to publishing, like reader’s behavior and content performance, and analyzes this data in real-time (sub-second latency between ingestion and data visualization). By collecting first-party raw data (no sampling & no aggregation), publishers get unprecedented flexibility in building their own metrics, reports, and different strategies for different kinds of content. This also allows publishers to quickly test hypotheses on both live and historical data. These dashboards and reports are shareable and customizable across teams making the workload on the analysts much lighter and gives them the ability to deliver what they want to deliver in the way they want and in lightning speeds! **Average Rating:** 4.4/5.0 **Total Reviews:** 10 #### How Do G2 Users Rate Deep.BI? - **Has the product been a good partner in doing business?:** 10.0/10 (Category avg: 8.9/10) - **Multi-Source Analysis:** 8.3/10 (Category avg: 8.5/10) - **Real-Time Analytics:** 7.5/10 (Category avg: 8.5/10) - **Data Workflow:** 7.5/10 (Category avg: 8.5/10) #### Who Is the Company Behind Deep.BI? - **Seller:** [Deep.BI](https://www.g2.com/sellers/deep-bi) - **Year Founded:** 2016 - **HQ Location:** San Francisco, California - **Twitter:** @\_DeepBI 962 Twitter followers - **LinkedIn® Page:** [www.linkedin.com](https://www.g2.com/external_clickthroughs/record?secure%5Bsource_type%5D=product_profile&secure%5Btoken%5D=cf8b636f916e02468a7c97feb497d1b8663730ad034645a4758c1f0a693dd006&secure%5Burl%5D=https%3A%2F%2Fwww.linkedin.com%2Fcompany%2Fdeep-bi%2F&secure%5Burl_type%5D=linkedin_company_website) 18 employees on LinkedIn® #### Who Uses This Product? - **Company Size:** 50% Small, 40% Medium #### What Do G2 Reviewers Say About Deep.BI? _AI-generated summary from verified user reviews_ ##### Pros - Users value the **real-time actionable insights** from Deep.BI, enhancing their ability to analyze customer interactions effectively. - Users value the **real-time actionable insights** from Deep.BI, enhancing their ability to understand customer behavior swiftly. - Users value the **real-time actionable insights** from Deep.BI, enhancing data-driven decision-making for their clients. - Users value the **real-time actionable insights** from Deep.BI, enhancing audience engagement through informed decision-making. - Users value the **automation capabilities** of Deep.BI, streamlining analytics and enhancing dashboard creation for clients. ##### Cons - Users find the **coding difficulty** in Deep.BI to be a barrier, complicating their usage of the platform. - Users find the **confusing interface** of Deep.BI challenging, especially for those without technical expertise. - Users find the **UI/UX not intuitive** , making it difficult for layman users to navigate and utilize effectively. - Users find the **poor interface design** challenging for layman users, affecting overall usability and experience. - Users find the **UI design lacking** , making it difficult for non-technical individuals to navigate the platform effectively. #### What Are Recent G2 Reviews of Deep.BI? **["Helpful real-time data processing"](https://www.g2.com/survey_responses/deep-bi-review-10032368)** **Rating:** 4.0/5.0 stars _— Frederic G._ [Read full review](https://www.g2.com/survey_responses/deep-bi-review-10032368) **["Useful for processing data and assessing reports in real time"](https://www.g2.com/survey_responses/deep-bi-review-10391757)** **Rating:** 4.0/5.0 stars _— Komal R._ [Read full review](https://www.g2.com/survey_responses/deep-bi-review-10391757) #### What Are G2 Users Discussing About Deep.BI? - [What is the three 3 capabilities of BIS business intelligence system?](https://www.g2.com/discussions/what-is-the-three-3-capabilities-of-bis-business-intelligence-system) - [What are the functions of BI systems?](https://www.g2.com/discussions/what-are-the-functions-of-bi-systems) - [What are the key capabilities of BI?](https://www.g2.com/discussions/what-are-the-key-capabilities-of-bi) ### [HyperAspect Cognitive Cloud](https://www.g2.com/products/hyperaspect-cognitive-cloud/reviews) HyperAspect Cognitive Cloud is an enterprise AI analytics and automation platform that empowers users to leverage big data to drive strategic, efficient decision-making across departments. We bring responsible AI and natural language processing into an organization's core processes with the required security compliance frameworks within data-intensive industries like healthcare, finance, insurance, legal, marketing, retail, professional digital services. **Average Rating:** 5.0/5.0 **Total Reviews:** 6 #### How Do G2 Users Rate HyperAspect Cognitive Cloud? - **Has the product been a good partner in doing business?:** 10.0/10 (Category avg: 8.9/10) - **Multi-Source Analysis:** 10.0/10 (Category avg: 8.5/10) - **Real-Time Analytics:** 9.6/10 (Category avg: 8.5/10) - **Data Workflow:** 10.0/10 (Category avg: 8.5/10) #### Who Is the Company Behind HyperAspect Cognitive Cloud? - **Seller:** [HyperAspect](https://www.g2.com/sellers/hyperaspect) - **Year Founded:** 2017 - **HQ Location:** Washinghton , US - **LinkedIn® Page:** [bg.linkedin.com](https://www.g2.com/external_clickthroughs/record?secure%5Bsource_type%5D=product_profile&secure%5Btoken%5D=558014f3ace026351fe23a3ed036483418ad8e3a490b0f4d98459b65a95050c1&secure%5Burl%5D=https%3A%2F%2Fbg.linkedin.com%2Fcompany%2Fhyperaspect&secure%5Burl_type%5D=linkedin_company_website) 11 employees on LinkedIn® #### Who Uses This Product? - **Company Size:** 67% Medium, 33% Small #### What Do G2 Reviewers Say About HyperAspect Cognitive Cloud? _AI-generated summary from verified user reviews_ ##### Pros - Users praise the **AI-driven insights** of HyperAspect Cognitive Cloud, enhancing their data analysis experience effortlessly. - Users praise the **user-friendly AI integration** of HyperAspect Cognitive Cloud, making advanced data analysis accessible to all. - Users appreciate the **user-friendly design** of HyperAspect Cognitive Cloud, making AI accessible for all skill levels. - Users benefit from the **helpful customer support** that simplifies implementation and enhances productivity with HyperAspect Cognitive Cloud. - Users value the **easy integrations** of HyperAspect Cognitive Cloud for quick deployments and enhanced productivity. ##### Cons - Users find the **pricing expensive** , making it less accessible for smaller businesses seeking cognitive solutions. - Users find the **pricing issues** challenging, especially for smaller businesses looking to adopt HyperAspect Cognitive Cloud. #### What Are Recent G2 Reviews of HyperAspect Cognitive Cloud? **["Very easy to work with"](https://www.g2.com/survey_responses/hyperaspect-cognitive-cloud-review-10712175)** **Rating:** 5.0/5.0 stars _— Atanas A._ [Read full review](https://www.g2.com/survey_responses/hyperaspect-cognitive-cloud-review-10712175) **["Very user friendly and effective Cloud Computing solution"](https://www.g2.com/survey_responses/hyperaspect-cognitive-cloud-review-10716137)** **Rating:** 5.0/5.0 stars _— Viktor I._ [Read full review](https://www.g2.com/survey_responses/hyperaspect-cognitive-cloud-review-10716137) ### [BellaDati](https://www.g2.com/products/belladati/reviews) Agile analytics and reporting tool, which enables business users to make informed decisions from real-time business data **Average Rating:** 3.5/5.0 **Total Reviews:** 4 #### How Do G2 Users Rate BellaDati? - **Has the product been a good partner in doing business?:** 8.3/10 (Category avg: 8.9/10) - **Multi-Source Analysis:** 6.7/10 (Category avg: 8.5/10) - **Real-Time Analytics:** 10.0/10 (Category avg: 8.5/10) - **Data Workflow:** 8.3/10 (Category avg: 8.5/10) #### Who Is the Company Behind BellaDati? - **Seller:** [BellaDati](https://www.g2.com/sellers/belladati) - **Year Founded:** 2013 - **HQ Location:** Singapore, SG - **Twitter:** @BellaDati 291 Twitter followers - **LinkedIn® Page:** [www.linkedin.com](https://www.g2.com/external_clickthroughs/record?secure%5Bsource_type%5D=product_profile&secure%5Btoken%5D=a8c0b2fb1a7af97cde8ee3cc32fae3dbe059ce3c255d9401459e101f85c5f559&secure%5Burl%5D=https%3A%2F%2Fwww.linkedin.com%2Fcompany%2Fbelladati&secure%5Burl_type%5D=linkedin_company_website) 14 employees on LinkedIn® - **Phone:** 866-668-0180 #### Who Uses This Product? - **Company Size:** 50% Large, 50% Small #### What Are Recent G2 Reviews of BellaDati? **["Very powerful BI tool at a fraction of the cost."](https://www.g2.com/survey_responses/belladati-review-412356)** **Rating:** 4.0/5.0 stars _— Verified User in Computer Software_ [Read full review](https://www.g2.com/survey_responses/belladati-review-412356) **["BellaDati IOT"](https://www.g2.com/survey_responses/belladati-review-5320786)** **Rating:** 5.0/5.0 stars _— Bobby Chakravarthy B._ [Read full review](https://www.g2.com/survey_responses/belladati-review-5320786) #### What Are G2 Users Discussing About BellaDati? - [What is BellaDati used for?](https://www.g2.com/discussions/what-is-belladati-used-for) ### [BIRD Analytics](https://www.g2.com/products/bird-analytics/reviews) Lightning fast insights at business scale! BIRD Analytics platform provides real time insights on any data, be it batch data or data-in-motion. With its cloud native full-stack capabilities, in-built scalable enterprise data warehouse, 100+ out-of-box connectors with readymade KPI driven dashboards, ERP accelerators and streaming/event driven capabilities, be rest assured that your investments are secured on the right technology platform for the near future. **Average Rating:** 4.9/5.0 **Total Reviews:** 6 #### How Do G2 Users Rate BIRD Analytics? - **Has the product been a good partner in doing business?:** 10.0/10 (Category avg: 8.9/10) - **Multi-Source Analysis:** 10.0/10 (Category avg: 8.5/10) - **Real-Time Analytics:** 9.4/10 (Category avg: 8.5/10) - **Data Workflow:** 10.0/10 (Category avg: 8.5/10) #### Who Is the Company Behind BIRD Analytics? - **Seller:** [BirdAnalytics](https://www.g2.com/sellers/birdanalytics) - **Year Founded:** 2014 - **HQ Location:** Newark, US - **Twitter:** @BIRDanalytics 71 Twitter followers - **LinkedIn® Page:** [www.linkedin.com](https://www.g2.com/external_clickthroughs/record?secure%5Bsource_type%5D=product_profile&secure%5Btoken%5D=d77f9f01adba5cd2424ab21bacc4bd8e3ad0c4ec451bf045f86ae80a2f2850ed&secure%5Burl%5D=https%3A%2F%2Fwww.linkedin.com%2Fcompany%2Fbirdanalytics%2Fabout%2F&secure%5Burl_type%5D=linkedin_company_website) 17 employees on LinkedIn® #### Who Uses This Product? - **Company Size:** 100% Medium #### What Are Recent G2 Reviews of BIRD Analytics? **["BIRD analytics is a fast, high performance AI integrated tools that provides you best solutions."](https://www.g2.com/survey_responses/bird-analytics-review-9503734)** **Rating:** 5.0/5.0 stars _— Chithra P._ [Read full review](https://www.g2.com/survey_responses/bird-analytics-review-9503734) **["BIRD analytics is a one of the fast and high performance AI integrated platform."](https://www.g2.com/survey_responses/bird-analytics-review-9503443)** **Rating:** 5.0/5.0 stars _— Kaushal K._ [Read full review](https://www.g2.com/survey_responses/bird-analytics-review-9503443) ### [CUBO iQ® Enterprise](https://www.g2.com/products/cubo-iq-enterprise/reviews) Globalization and the emergence of new applications demand accurate correlations between entity records, which have been expressed with different schemas, formats, fields, and attributes. In a private entity, a single view of their customers is essential for Business Intelligence (BI) and more. Identity resolution is also used in applications related to data quality, such as Customer Data Management (CDM) and Master Data Management (MDM). In contexts like national security, it is possible to identify dangerous profiles through screening for patterns, providing real-time visible matches. In the case of financial services, it can identify customers associated with illicit activities such as terrorism, money laundering, and fraud (by conducting background checks). Most developed countries require compliance with Know Your Customer (KYC), Politically Exposed Person (PEP), and Office of Foreign Assets Control (OFAC) regulations. For the healthcare sector, it enables the construction of a comprehensive picture of patient-related information. The capabilities of automated identity resolution are accurate, fast, and scalable, specifically addressing these and other entity matching requirements. Vision. **Average Rating:** 4.5/5.0 **Total Reviews:** 5 #### How Do G2 Users Rate CUBO iQ® Enterprise? - **Has the product been a good partner in doing business?:** 8.3/10 (Category avg: 8.9/10) - **Multi-Source Analysis:** 6.7/10 (Category avg: 8.5/10) - **Real-Time Analytics:** 8.3/10 (Category avg: 8.5/10) - **Data Workflow:** 6.1/10 (Category avg: 8.5/10) #### Who Is the Company Behind CUBO iQ® Enterprise? - **Seller:** [Datos Maestros™](https://www.g2.com/sellers/datos-maestros) - **Year Founded:** 2019 - **HQ Location:** Bogotá, CO - **LinkedIn® Page:** [linkedin.com](https://www.g2.com/external_clickthroughs/record?secure%5Bsource_type%5D=product_profile&secure%5Btoken%5D=e67d1b7c65cd09d7671156b7f5ca393458b2024c81126b965c501ccadbcd082d&secure%5Burl%5D=https%3A%2F%2Flinkedin.com%2Fcompany%2Fdatosmaestros&secure%5Burl_type%5D=linkedin_company_website) 13 employees on LinkedIn® #### Who Uses This Product? - **Company Size:** 80% Small, 20% Medium #### What Are Recent G2 Reviews of CUBO iQ® Enterprise? **["Ease of use"](https://www.g2.com/survey_responses/cubo-iq-enterprise-review-9545492)** **Rating:** 4.5/5.0 stars _— José Miguel S._ [Read full review](https://www.g2.com/survey_responses/cubo-iq-enterprise-review-9545492) **["CUBO iQ an excellent tool for Data Governance"](https://www.g2.com/survey_responses/cubo-iq-enterprise-review-9520160)** **Rating:** 4.5/5.0 stars _— Fredy Yarney R._ [Read full review](https://www.g2.com/survey_responses/cubo-iq-enterprise-review-9520160) ### [Jethro](https://www.g2.com/products/jethro/reviews) Jethro makes interactive Business Intelligence work on Big Data. (Hadoop). Jethro enables Business Intelligence users to analyze and visualize Big Data in real-time and its SQL Acceleration Engine seamlessly integrates with BI tools like Tableau or Qlik. **Average Rating:** 4.5/5.0 **Total Reviews:** 3 #### How Do G2 Users Rate Jethro? - **Has the product been a good partner in doing business?:** 8.3/10 (Category avg: 8.9/10) - **Multi-Source Analysis:** 8.9/10 (Category avg: 8.5/10) - **Real-Time Analytics:** 7.8/10 (Category avg: 8.5/10) - **Data Workflow:** 7.8/10 (Category avg: 8.5/10) #### Who Is the Company Behind Jethro? - **Seller:** [Jethro](https://www.g2.com/sellers/jethro) - **Year Founded:** 2012 - **HQ Location:** San Francisco, US - **Twitter:** @JethroData 1,999 Twitter followers - **LinkedIn® Page:** [www.linkedin.com](https://www.g2.com/external_clickthroughs/record?secure%5Bsource_type%5D=product_profile&secure%5Btoken%5D=dd2fd8ba76c892d2a86a7ab03af5c749c225437b06fe6f2747e60db7ed7cb419&secure%5Burl%5D=https%3A%2F%2Fwww.linkedin.com%2Fcompany%2F2894649&secure%5Burl_type%5D=linkedin_company_website) 45 employees on LinkedIn® #### Who Uses This Product? - **Company Size:** 67% Large, 33% Small #### What Do G2 Reviewers Say About Jethro? _AI-generated summary from verified user reviews_ ##### Pros - Users value the **ease of use** with Jethro, appreciating its intuitive interface and seamless indexing features. - Users value the **fast querying** capabilities of Jethro, significantly reducing time for processing large data sets. - Users value the **accelerated performance** of Jethro, which significantly reduces query time for large datasets. - Users highlight the **powerful dynamic indexing** of Jethro, greatly enhancing performance and scalability. - Users value the **horizontal scaling** capability of Jethro, enhancing performance and flexibility for large data sets. ##### Cons - Users find Jethro to be **expensive** , especially for small organizations with limited data needs and high maintenance costs. - Users find the **setup complexity** of Jethro challenging, alongside high hardware requirements and costly maintenance. - Users find the **difficult setup** process challenging, impacting their initial experience with Jethro. - Users often face **maintenance issues** due to complexity, costs, and high hardware requirements affecting performance. #### What Are Recent G2 Reviews of Jethro? **["Jethro data processing use case"](https://www.g2.com/survey_responses/jethro-review-10492071)** **Rating:** 4.0/5.0 stars _— Anand J._ [Read full review](https://www.g2.com/survey_responses/jethro-review-10492071) **["very powerful software!"](https://www.g2.com/survey_responses/jethro-review-10281847)** **Rating:** 4.5/5.0 stars _— Ling G._ [Read full review](https://www.g2.com/survey_responses/jethro-review-10281847) #### What Are G2 Users Discussing About Jethro? - [What is Jethro used for?](https://www.g2.com/discussions/jethro-what-is-jethro-used-for) - [What is Jethro used for?](https://www.g2.com/discussions/what-is-jethro-used-for) ### [Polyture](https://www.g2.com/products/polyture/reviews) Polyture combines all the major elements of the modern data stack into one application that is intuitive and free to use. The platform consists of four modules; Warehousing, Dataflows, Automated Machine Learning, and Dashboards. **Average Rating:** 5.0/5.0 **Total Reviews:** 4 #### Who Is the Company Behind Polyture? - **Seller:** [Polyture](https://www.g2.com/sellers/polyture) - **HQ Location:** Santa Clara, CA - **Twitter:** @PolytureData 25 Twitter followers - **LinkedIn® Page:** [www.linkedin.com](https://www.g2.com/external_clickthroughs/record?secure%5Bsource_type%5D=product_profile&secure%5Btoken%5D=7886df2ed926834e5eb248c77dcfa8e5c815d3ab1f0fe3132ced0dba45868834&secure%5Burl%5D=https%3A%2F%2Fwww.linkedin.com%2Fcompany%2FNo-Linkedin-Presence-Added-Intentionally-By-DataOps&secure%5Burl_type%5D=linkedin_company_website) 1 employees on LinkedIn® #### Who Uses This Product? - **Company Size:** 100% Small #### What Are Recent G2 Reviews of Polyture? **["Great for making live dashboards from Google Sheets"](https://www.g2.com/survey_responses/polyture-review-5129091)** **Rating:** 5.0/5.0 stars _— George C._ [Read full review](https://www.g2.com/survey_responses/polyture-review-5129091) **["The best tool we've found for our company data"](https://www.g2.com/survey_responses/polyture-review-5059135)** **Rating:** 5.0/5.0 stars _— Kamal M._ [Read full review](https://www.g2.com/survey_responses/polyture-review-5059135) #### What Are G2 Users Discussing About Polyture? - [What is Polyture used for?](https://www.g2.com/discussions/what-is-polyture-used-for) ### [Website Development, Web Development, Product Development](https://www.g2.com/products/website-development-web-development-product-development/reviews) About Incentius: A new age technology company that creates innovative could-enabled business intelligent solutions & out-of-the-box platforms for startups using secure & scalable technologies. We are a product engineering & data analytics services provider for next-generation enterprise growth management, enabling innovation using secure technologies and standard enterprise products. **Average Rating:** 4.7/5.0 **Total Reviews:** 3 #### How Do G2 Users Rate Website Development, Web Development, Product Development? - **Has the product been a good partner in doing business?:** 10.0/10 (Category avg: 8.9/10) - **Multi-Source Analysis:** 8.3/10 (Category avg: 8.5/10) - **Real-Time Analytics:** 9.2/10 (Category avg: 8.5/10) - **Data Workflow:** 8.3/10 (Category avg: 8.5/10) #### Who Is the Company Behind Website Development, Web Development, Product Development? - **Seller:** [Incentius](https://www.g2.com/sellers/incentius) - **Year Founded:** 2013 - **HQ Location:** Pune, IN - **LinkedIn® Page:** [www.linkedin.com](https://www.g2.com/external_clickthroughs/record?secure%5Bsource_type%5D=product_profile&secure%5Btoken%5D=a3eb370b3e5b069ada584e4901e39af5bd754b83d8f2823e53882b48fa6293e7&secure%5Burl%5D=https%3A%2F%2Fwww.linkedin.com%2Fcompany%2Fincentius&secure%5Burl_type%5D=linkedin_company_website) 40 employees on LinkedIn® #### Who Uses This Product? - **Company Size:** 67% Small, 33% Medium #### What Do G2 Reviewers Say About Website Development, Web Development, Product Development? _AI-generated summary from verified user reviews_ ##### Pros - Users appreciate the **easy learning** of the product, as it saves time and simplifies explanations. - Users appreciate the **time-saving** benefits of the product, making descriptions and explanations effortless and efficient. #### What Are Recent G2 Reviews of Website Development, Web Development, Product Development? **["Web Development, Product Development is the best platform to develop a website for my own company"](https://www.g2.com/survey_responses/website-development-web-development-product-development-review-9436447)** **Rating:** 5.0/5.0 stars _— Parameswar C._ [Read full review](https://www.g2.com/survey_responses/website-development-web-development-product-development-review-9436447) **["Best tools for web development"](https://www.g2.com/survey_responses/website-development-web-development-product-development-review-10705020)** **Rating:** 5.0/5.0 stars _— Aman K._ [Read full review](https://www.g2.com/survey_responses/website-development-web-development-product-development-review-10705020) ### [CelerData Cloud](https://www.g2.com/products/celerdata-cloud/reviews) CelerData Cloud is the fastest, secure analytical engine that powers customer-facing and AI-driven analytics at scale, delivering consistently reliable and unbeatable performance with a future-proof architecture—ensuring real-time access to open data without ingestion delays or costly data pipelines. Powered by StarRocks, CelerData delivers 3X the performance/cost of any other solution on the market and is the only platform uniquely designed to enable users to simplify their lakehouse architecture and ditch the need for a data warehouse. CelerData is used worldwide by market-leading brands including Coinbase, Pinterest, Demandbase, and Expedia to generate critical new insights for these data-driven companies. **Average Rating:** 4.8/5.0 **Total Reviews:** 3 #### How Do G2 Users Rate CelerData Cloud? - **Has the product been a good partner in doing business?:** 10.0/10 (Category avg: 8.9/10) - **Real-Time Analytics:** 10.0/10 (Category avg: 8.5/10) #### Who Is the Company Behind CelerData Cloud? - **Seller:** [CelerData](https://www.g2.com/sellers/celerdata) - **Year Founded:** 2022 - **HQ Location:** Menlo Park, US - **LinkedIn® Page:** [www.linkedin.com](https://www.g2.com/external_clickthroughs/record?secure%5Bsource_type%5D=product_profile&secure%5Btoken%5D=7b55c698292526ff0f29a160acbccbbcf7af7f19294ac7203dd3473fc9d51e40&secure%5Burl%5D=https%3A%2F%2Fwww.linkedin.com%2Fcompany%2Fstarrocks&secure%5Burl_type%5D=linkedin_company_website) 65 employees on LinkedIn® #### Who Uses This Product? - **Company Size:** 67% Small, 33% Large #### What Do G2 Reviewers Say About CelerData Cloud? _AI-generated summary from verified user reviews_ ##### Pros - Users appreciate the **world-class customer support** from CelerData Cloud, enhancing their overall data management experience. - Users value the **extraordinarily fast query performance** of CelerData Cloud, enhanced by excellent support for their data needs. - Users praise the **incredibly fast query performance** and strong support of CelerData Cloud, enhancing their data strategy. - Users appreciate the **fast communication** of CelerData Cloud, enhancing data strategy transformation with swift support and query performance. - Users value the **incredibly fast query performance** of CelerData Cloud, which enhances their data strategy significantly. #### What Are Recent G2 Reviews of CelerData Cloud? **["Transforming Big Data with StarRocks"](https://www.g2.com/survey_responses/celerdata-cloud-review-11609872)** **Rating:** 5.0/5.0 stars _— Emre K._ [Read full review](https://www.g2.com/survey_responses/celerdata-cloud-review-11609872) **["A powerful SQL engine for your most demanding workloads"](https://www.g2.com/survey_responses/celerdata-cloud-review-11630143)** **Rating:** 4.5/5.0 stars _— Ye Z._ [Read full review](https://www.g2.com/survey_responses/celerdata-cloud-review-11630143) - [‹ Prev‹ Prev](/categories/big-data-analytics?order=g2_score&page=2&scid=It-JG6svAa#product-list) - [1](/categories/big-data-analytics?order=g2_score&scid=It-JG6svAa#product-list) - [2](/categories/big-data-analytics?order=g2_score&page=2&scid=It-JG6svAa#product-list) - 3 - [4](/categories/big-data-analytics?order=g2_score&page=4&scid=It-JG6svAa#product-list) - [5](/categories/big-data-analytics?order=g2_score&page=5&scid=It-JG6svAa#product-list) - [6](/categories/big-data-analytics?order=g2_score&page=6&scid=It-JG6svAa#product-list) - [7](/categories/big-data-analytics?order=g2_score&page=7&scid=It-JG6svAa#product-list) - [8](/categories/big-data-analytics?order=g2_score&page=8&scid=It-JG6svAa#product-list) - [Next ›Next ›](/categories/big-data-analytics?order=g2_score&page=4&scid=It-JG6svAa#product-list) Spotlight Categories [Contact Center Workforce Software](https://www.g2.com/categories/contact-center-workforce) [Third Party & Supplier Risk Management Software](https://www.g2.com/categories/third-party-supplier-risk-management) [Lead Intelligence Software](https://www.g2.com/categories/lead-intelligence) [Contact Center Quality Assurance Software](https://www.g2.com/categories/contact-center-quality-assurance) [Generative AI Infrastructure Software](https://www.g2.com/categories/generative-ai-infrastructure) Similar Categories - [Big Data Processing and Distribution](/categories/big-data-processing-and-distribution) - [Event Stream Processing](/categories/event-stream-processing) [Browse Big Data Analytics Themes](/categories/big-data-analytics/themes) ![Bijou Barry](/assets/transparent-ad5be28fbcd25b7b08d2cebe1d957125437fb5407d75ee717965ad22c8808791.gif "Bijou Barry") BB Researched and written by [Bijou Barry](https://research.g2.com/insights/author/bijou-barry) Updated April 9, 2026 Big data analytics software provides insights into large, complex data sets collected from big data clusters, helping business users understand data trends, patterns, and anomalies through visualizations, reports, and dashboards, often requiring query languages to extract data from unstructured file systems. ### Core Capabilities of Big Data Analytics Software To qualify for inclusion in the Big Data Analytics category, a product must: - Consume data, query file systems, and connect directly to big data clusters - Allow users to prepare complex big data sets into helpful and understandable data visualizations - Create business-applicable reports, visualizations, and dashboards based on discoveries inside the data sets ### Common Use Cases for Big Data Analytics Software Data engineers, analysts, and business intelligence teams use big data analytics software to extract value from large-scale, unstructured data environments. Common use cases include: - Querying and analyzing large Hadoop or distributed data clusters to surface business insights - Detecting patterns and anomalies in high-volume data sets for operational or strategic decision-making - Building self-service charts and dashboards for non-technical stakeholders from big data sources ### How Big Data Analytics Software Differs from Other Tools Big data analytics software is solely focused on manipulating complex, large-scale data clusters into understandable visualizations, differentiating it from [analytics platforms](https://www.g2.com/categories/analytics-platforms), which support a wide range of data sources and connectors beyond big data. The two categories are mutually exclusive. Big data analytics tools are commonly used at companies running Hadoop in conjunction with [big data processing and distribution software](https://www.g2.com/categories/big-data-processing-and-distribution) and integrate with [data warehouse software](https://www.g2.com/categories/data-warehouse) as the central hub for integrated data. Some solutions also leverage [machine learning](https://www.g2.com/categories/machine-learning) and [natural language processing](https://www.g2.com/categories/natural-language-processing-nlp) to enable natural language querying. ### Insights from G2 on Big Data Analytics Software Based on category trends on G2, query flexibility and scalability for large data sets stand out as standout capabilities. Faster insight generation from complex data environments stand out as the primary benefit of adoption. Show More * * * ## How Do You Choose the Right Big Data Analytics Software? ### What You Should Know About Big Data Analytics Software ### What is Big Data Analytics Software? The huge amount of data that is accessible to businesses today has made it a near necessity for them to implement some type of analytics software to better understand and act on that data. Implementing big data analytics software has been a major 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 data sets collected from big data clusters. With the ability to visualize and understand business data, employees can make informed decisions. For example, retailers can use these tools to better understand inventory distribution across their channels and make data-driven decisions based on this data. Some big data analytics solutions may offer artificial intelligence or machine learning features, such as natural language processing, as an interface capability to further aid nontechnical users. #### What Types of Big Data Analytics Software Exist? Many types of big data analytics solutions share overlapping functionality, while simultaneously catering to different user personas such as data analysts and financial analysts or providing unique services. Because of the unstructured nature of big data clusters, these analytics solutions require a query language to pull the data out of the file system. Most commercial table databases allow SQL queries; however, big data analytics tools do not necessarily offer such SQL language capabilities and may require a more intricate knowledge of querying from a data scientist. As an alternative, some solutions may offer self-service features so that the average employee can assemble their own charts and graphs from big data sets. **Self-service big data analytics tools** Self-service big data analytics tools do not require coding knowledge, so end users with limited to no coding knowledge can take advantage of them for data needs. This enables business users like sales representatives, human resource managers, marketers, and other nondata team members to make decisions based on relevant business data. Self-service solutions often provide drag-and-drop functionality for building dashboards, prebuilt templates for querying data, and, occasionally, natural language querying for data discovery. Similar to [analytics platforms](https://www.g2.com/categories/analytics-platforms), organizations use these tools to build interactive dashboards for discovering actionable insights.  **Embedded analytics solutions** Embedded analytics solutions offer the ability to integrate proprietary analytics functionality within other business applications. Commonly, businesses embed analytics solutions in software such as CRMs, ERP, and portals (e.g., intranets or extranets). 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 take advantage of data for improved decision making. ** ** ### What are the Common Features of Big Data Analytics Software? Big data analytics software helps companies get a better understanding of their data. The following are some core features of this software:  **Data connectivity:** If businesses cannot connect the requisite data, then there is no use for big data analytics software. The methods for connecting data include Hadoop and [Spark integration](https://www.g2.com/categories/big-data-analytics/f/spark-integration) which allows for processing and distribution workflows on top of Apache Hadoop and Apache Spark, respectively. In addition, this software should allow for analyzing data that is stored in [data lakes](https://www.g2.com/categories/big-data-analytics/f/data-lake), data warehouses, and data lake houses. **Data transformation:** For data to be analyzed, it needs to be properly cleaned and transformed into a usable format. Big data analytics software provides features such as real-time analytics and data querying. With these features, businesses can gain a high-level view of their data in real time, allowing one to query it and better understand it. Through query languages like SQL, users can query their data and dig deeper into particular data sets and data points. **Data operations:** Once the data is connected (or integrated) and transformed, it can be analyzed. Firstly, it is important to establish data workflows, which can help in stringing together specific functions and data sets to automate analytics iterations. In addition, big data analytics software provides the ability to visualize data through dashboards, as well as [notebooks](https://www.g2.com/categories/big-data-analytics/f/notebooks) which can be used to create visualization with predefined or scheduled queries.  It is not always the case that one will access analytics via a standalone analytics platform. Therefore, some products provide [embedded analytics capabilities](https://www.g2.com/categories/big-data-analytics/f/embedded-analytics). This allows users to access analytics inside business applications, which allows for more streamlined work since the users need not switch between applications.  Other Features of Big Data Analytics Software: [Governed Discovery](https://www.g2.com/categories/big-data-analytics/f/governed-discovery), ### What are the Benefits of Big Data Analytics Software? Data is both common and invaluable and within that data lies insights that could impact an organization's processes and performance. There are seemingly infinite insights a business can pull from their data and numerous reasons to utilize big data analytics software.  Big data analytics software helps people make decisions easier by allowing teams to gain deeper insight into their data. With increased data literacy, teams across a business, from sales to marketing to finance can become more efficient and better understand how they can improve through data-driven initiatives.  With big data analytics software, businesses can ingest, integrate, and prepare big data sources. Subsequently, they can connect all company data sources into a single platform to make cross-department connections, visualize and understand company data, encourage data-driven decision making for business optimization, and discover new insights that can enhance the bottom line. **Enable data-driven decision making:** Businesses can use big data analytics software to fuel digital transformation by leveraging data to drive business decisions. Companies can leverage analytics and business intelligence (BI) tools to understand all aspects of the business, including hiring forecasts, which marketing campaign should be used to target certain demographics, which sales prospects to target first, supply chain optimization, and many others. **Measure and understand company performance:** Organizations often leverage data visualization tools to track company key performance indicators (KPIs) in real time. From there, big data analytics software can be used to determine why the business is either exceeding or falling short of those important company metrics. When stakeholders develop a keen understanding of why the business is performing the way it is, they can make adjustments and pivots; if a team is falling short of a goal, they can examine and adjust processes as needed. It is one thing to simply know the performance of sales or web traffic numbers, but it is another to dig into the reasons behind it and adapt based on what is successful and what is not. **Discover new actionable insights:** Analytics tools combine data from a variety of sources, including [accounting software](https://www.g2.com/categories/accounting), [enterprise resource planning (ERP) software](https://www.g2.com/categories/erp), [CRM software](https://www.g2.com/categories/crm),[marketing automation software](https://www.g2.com/categories/marketing-automation), and others. Data analysts can leverage this integrated data to find correlations between different departments, and their processes and actions, to discover previously hidden insights. For example, it is possible that certain sales tactics have varying impacts on the numbers for one specific product versus another.  Analysts can discover this impact by comparing the list of closed accounts from their company CRM with products shipped in their ERP system. Teams are generally siloed and use disparate software, so these insights that were traditionally more difficult to discover, are now made easier.  ### Who Uses Big Data Analytics Software? **Data analysts:** Depending on the complexity of the software, it is likely that analysts will be required. They can help set up the requisite queries, dashboards, and notebooks for other employees and teams. They can create complex queries inside the platforms to gather a deeper understanding of business-critical data. **Operations and supply chain teams:** A company’s supply chain frequently has many touchpoints, and as a result, many data points. Therefore, employees working in operations and supply chain teams are able to use big data analytics software to gain a better understanding of their departments and the data that is generated, such as from an ERP system. These applications track everything from accounting to supply chain and distribution; by inputting supply chain data into this software, supply chain managers can optimize a number of processes to save time and resources. **Finance teams:** Finance teams leverage big data analytics software to gain insight and understanding into the factors that impact an organization's bottom line. Through integrations with financial systems such as [accounting software](https://www.g2.com/categories/accounting), employees such as chief financial officers (CFOs) can see how well the business is performing. As mentioned above, these employees will likely be accessing the software via self-service dashboards that were set up by data analysts. By integrating financial data with sales, marketing, and other operations data, accounting and finance teams pull actionable insights that might not have been uncovered through the use of traditional tools. **Sales and marketing teams:** Sales teams also seek to improve financial metrics and can benefit tremendously from being more data-driven. Through the use of both self-service analytics tools and embedded analytics solutions, they can 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. For marketing teams, tracking the performance of campaigns is key. Since they 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. **Consultants:** Businesses do not always have the luxury to build, develop, and optimize their own analytics solutions. Some businesses opt to employ external consultants, such as [business intelligence (BI) consulting providers](https://www.g2.com/categories/business-intelligence-bi-consulting). These providers seek to understand a business and its goals, interpret data, and offer advice to ensure goals are met. BI consultants frequently have industry-specific knowledge alongside their technical backgrounds, with experience in healthcare, business, and other fields.  ### What are the Alternatives to Big Data Analytics Software? Alternatives to big data analytics software can replace this type of software, either partially or completely: [Analytics platforms](https://www.g2.com/categories/analytics-platforms) **:** Analytics platforms might include big data integrations, but are broader-focused tools that facilitate the following five elements: data preparation, data modeling, data blending, data visualization, and insights delivery. [Log analysis software](https://www.g2.com/categories/log-analysis): Businesses that are focused on log data might benefit from deploying log analysis software, which is used to analyze log data from applications and systems. It should be kept in mind that this software is much more limited in terms of data types and data sources to which it can be connected to. However, since log analysis software focuses on logs, it frequently provides more granular details around log-related data. [Stream analytics software](https://www.g2.com/categories/stream-analytics) **:** When one is looking for tools specifically geared toward analyzing data in real time, stream analytics software is a go-to solution. These tools help users analyze data in transfer through APIs, between applications, and more. This software can be helpful with internet of things (IoT) data, which one frequently wants to analyze in real time. [Predictive analytics software](https://www.g2.com/categories/predictive-analytics): Broad-purpose big data analytics software allows businesses to conduct various forms of analysis, such as prescriptive, descriptive, and predictive. Businesses that are focused on looking at their past and present data to predict future outcomes can use predictive analytics software for a more finetuned solution.  [Text analysis software](https://www.g2.com/categories/text-analysis): Big data analytics software is focused on structured or numerical data, allowing users to drill down and dig into numbers to inform business decisions. If the user is looking to focus on unstructured or text data, text analysis solutions are the best bet. These tools help users quickly understand and pull sentiment analysis, key phrases, themes, and other insights from unstructured text data. #### Software Related to Big Data Analytics Software Related solutions that can be used together with big data analytics software include: [Data warehouse software](https://www.g2.com/categories/data-warehouse) **:** Most companies have a large number of disparate data sources, so to best integrate all their data, they implement a data warehouse. Data warehouses can house data from multiple databases and business applications, which allows BI and analytics tools to pull all company data from a single repository. This organization is critical to the quality of the data that is ingested by analytics software. [Data preparation software](https://www.g2.com/categories/data-preparation) **:** A key solution necessary for easy data analysis is a data preparation tool and other related data management tools. These solutions allow users to discover, combine, clean, and enrich data for simple analysis. Data preparation tools are often used by IT teams or data analysts tasked with using BI tools. Some BI platforms offer data preparation features, but businesses with a wide range of data sources often opt for a dedicated preparation tool. ### Challenges with Big Data Analytics Software Software solutions can come with their own set of challenges.  **Need for skilled employees:** Big data analytics software is not necessarily simple. Often, these tools require a dedicated administrator to help implement the solution and assist others with adoption. However, there is a shortage of skilled data scientists and analysts that are equipped to set up such solutions. Additionally, those same data scientists will be tasked with deriving actionable insights from within the data.  Without people skilled in these areas, businesses cannot effectively leverage the tools or their data. Even the self-service tools, which are to be used by the average business user, require someone to help deploy them. Companies can turn to vendor support teams or third-party consultants to assist if they are unable to bring someone in house. **Data organization:** To get the most of analytics solutions, that data needs to be organized. This means that databases should be set up correctly and integrated properly. This may require building a data warehouse, which can store data from a variety of applications and databases in a central location.  Businesses may need to purchase a dedicated [data preparation software](https://www.g2.com/categories/data-preparation) as well to ensure that data is joined and is clean for the analytics solution to consume in the right way. In the context of big data, a company might want to specifically consider big data processing and distribution software. This often requires a skilled data analyst, IT employee, or an outside consultant to help ensure data quality is at its finest for easy analysis. **User adoption:** It is not always easy to transform a business into a data-driven company. Particularly at more established companies that have done things the same way for years, it is not simple to force analytics tools upon employees, especially if there are ways for them to avoid it. If there are other options, such as spreadsheets or existing tools that employees can use instead of analytics software, they will most likely go that route. However, if managers and leaders ensure that analytics tools are a necessity in an employee’s day to day, then adoption rates will increase. ### Which Companies Should Buy Big Data Analytics Software? As has often been said, data is the fuel that drives modern businesses. Although it is cliche, it no doubt has truth to it. Therefore, businesses across the globe and across industries should consider some sort of analytics solution, such as big data analytics in order to make sense of that data and begin to make data-driven decisions.  **Financial services:** Within financial institutions, such as insurance brokerages, banks, and credit unions, it is common for a host of different systems to be used. These companies have data ranging from customer records, to transactions, to market data, and more. With the proliferation of systems comes more data. With a robust analytics solution in place, they can get a better understanding of the data that is being produced from the various systems across the business. As an industry that is heavily regulated, users can benefit from governed access capabilities which can be particularly beneficial, since it can assist in auditing company processes. **Healthcare:** Within the space of healthcare, bad data practices might have dire or even deadly consequences. Big data analytics software can help these organizations with having an overarching view of their data, such as patient records, insurance claims, finances, and more. Through the implementation of analytics, healthcare companies can lower risk and costs, and make their billing and collections smarter. **Retail** : Retail organizations, whether they be B2C, B2B, D2C, or others, rely on data to make informed decisions. For example, a seller of printers, in order to run a successful business, must keep track of many things such as their inventory, sales, their sales team, and returns. If all of this data is kept siloed within different systems, there is no single source of truth and departments cannot have a conversation around the actual state of the business’ data. With big data analytics software set up and connected to all of the relevant data sources, any retail business can see benefits and make meaningful data-driven decisions. ### How to Buy Big Data Analytics Software #### Requirements Gathering (RFI/RFP) for Big Data Analytics Software If a company is just starting out on their analytics journey, g2.com can help in selecting the best software for the particular company and use case. Since the particular solution might vary based on company size and industry, G2 is a great place to sort and filter reviews based on these criteria, along with many more. As mentioned above, the variety, volume, and velocity of data are vast. Therefore, users should think about how the particular solution fits their particular needs, as well as their future needs as they accumulate more data.  To find the right solution, buyers should determine 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 who will need to use this software, as this drives the number of licenses they are likely to 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 serves as a detailed guide that includes both 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 scope of the deployment, it might be helpful to produce a request for information (RFI), a one-page list with a few bullet points describing what is needed from a big data analytics software. #### Compare Big Data Analytics Software Products **Create a long list** From meeting the business functionality needs to implementation, vendor evaluations are an essential part of 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 down the list of vendors and come up with a shorter list of contenders, preferably no more than three to five. With this list in hand, 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 data sets. This will allow the business to evaluate like for like and see how each vendor stacks up against the competition.  #### Selection of Big Data Analytics Software **Choose a selection team** As big data analytics software is all about the data, the user must make sure that the selection process is data driven as well. The selection team should compare notes and facts and figures which 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 not negotiable (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 give a discount for multi-year contracts or for recommending 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 well received, the buyer can be confident that the selection was correct. If not, it might be time to go back to the drawing board. ### What Does Big Data Analytics Software Cost? Businesses decide to deploy big data analytics software with the goal of deriving some degree of a return on investment (ROI). #### Return on Investment (ROI) As they are looking to recoup their losses that they spent on the software, it is critical to understand the costs associated with it. As mentioned above, this software is typically billed per user, which is sometimes tiered depending on the company size. More users will typically translate into more licenses, which means more money. Users must consider how much is spent and compare that to what is gained, both in terms of efficiency as well as revenue. Therefore, businesses can compare processes between pre- and post-deployment of the software to better understand 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 their use of the big data analytics tool. ### Implementation of Big Data Analytics Software **How is Big Data 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 that be an implementation specialist from the vendor or a third-party consultancy. With vast experience, they can help businesses understand how to connect and consolidate their data sources and how to use the software efficiently and effectively. **Who is Responsible for Big Data Analytics Software Implementation?** It may require a lot of people, or many teams, to properly deploy an analytics platform. This is because data can cut across teams and functions. As a result, it is rare that one person or even one team has a full understanding of all of a company’s data assets. With a cross-functional team in place, a business can piece together their data and begin the journey of analytics, starting with proper data preparation and management. ### Big Data Analytics Software Trends **Data literacy** Business data is no longer locked up in silos. With big data analytics solutions, more users across a business can find, access, and analyze this data. In addition, [artificial intelligence (AI) software](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 easier and more powerful, providing more accurate results. Implementing analytics software has been a major 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 data sets collected from all their various sources. **Shift to the cloud** The move from on-premises data analytics to the cloud has been underway for a number of 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 insights. The move away from on-premises infrastructure has helped many companies enable data work anywhere one has access to the cloud—anywhere with internet access.  **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 are looking for using intuitive language. Intuitive methods of querying data mean enabling 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 whole data journey, from ingestion to insights. From AI-powered data preparation to smart insights, in which the platform suggests visualizations to the end user, big data analytics solutions are quickly becoming more powerful. Machine learning is helping end users discover hidden insights, allowing them to make sense of data and helping them to understand what they are seeing.