# Best Enterprise Data Preparation Software

  *By [Shalaka Joshi](https://research.g2.com/insights/author/shalaka-joshi)*

   Products classified in the overall Data Preparation category are similar in many regards and help companies of all sizes solve their business problems. However, enterprise business features, pricing, setup, and installation differ from businesses of other sizes, which is why we match buyers to the right Enterprise Business Data Preparation to fit their needs. Compare product ratings based on reviews from enterprise users or connect with one of G2's buying advisors to find the right solutions within the Enterprise Business Data Preparation category.

In addition to qualifying for inclusion in the Data Preparation Software category, to qualify for inclusion in the Enterprise Business Data Preparation Software category, a product must have at least 10 reviews left by a reviewer from an enterprise business.





## Category Overview

**Total Products under this Category:** 102


## Trust & Credibility Stats

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

- 30 Analysts and Data Experts
- 10,300+ Authentic Reviews
- 102+ 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.


## Top-Rated Products (Ranked by G2 Score)
  ### 1. [Tableau](https://www.g2.com/products/tableau/reviews)
  Tableau is the world’s leading AI-powered analytics platform. Whether you are a business user or an analyst, Tableau turns trusted data into actionable insights. With our flexible, interoperable platform, you can: Turn data into action at scale with human and agent collaboration. Tableau Next delivers agentic AI for faster data-insight-action workflows. It surfaces insights, provides proactive recommendations, and helps you take action in the flow of work. Scale data-driven insights with complete operational confidence. Tableau Cloud enables fully managed analytics at scale. It accelerates your time to value and gives you access to the latest AI-powered innovations. Deploy visual, self-service analytics with unmatched control and flexibility. Tableau Server meets your organization's governance and security needs. It provides enterprise-grade, self-service analytics on-premise or in your private cloud.


  **Average Rating:** 4.4/5.0
  **Total Reviews:** 3,495

**User Satisfaction Scores:**

- **Has the product been a good partner in doing business?:** 8.5/10 (Category avg: 9.0/10)
- **Data Workflows:** 8.4/10 (Category avg: 8.8/10)
- **Profiling and Classification:** 8.2/10 (Category avg: 8.5/10)
- **Data Joining:** 8.5/10 (Category avg: 8.9/10)


**Seller Details:**

- **Seller:** [Salesforce](https://www.g2.com/sellers/salesforce)
- **Company Website:** https://www.salesforce.com/
- **Year Founded:** 1999
- **HQ Location:** San Francisco, CA
- **Twitter:** @salesforce (581,281 Twitter followers)
- **LinkedIn® Page:** https://www.linkedin.com/company/3185/ (88,363 employees on LinkedIn®)

**Reviewer Demographics:**
  - **Who Uses This:** Data Analyst, Business Analyst
  - **Top Industries:** Information Technology and Services, Computer Software
  - **Company Size:** 41% Enterprise, 35% Mid-Market


#### Pros & Cons

**Pros:**

- Ease of Use (634 reviews)
- Data Visualization (563 reviews)
- Visualization (424 reviews)
- Features (351 reviews)
- Intuitive (317 reviews)

**Cons:**

- Learning Curve (282 reviews)
- Learning Difficulty (240 reviews)
- Expensive (225 reviews)
- Slow Performance (155 reviews)
- Difficulty (139 reviews)

  ### 2. [Alteryx](https://www.g2.com/products/alteryx/reviews)
  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.


  **Average Rating:** 4.6/5.0
  **Total Reviews:** 648

**User Satisfaction Scores:**

- **Has the product been a good partner in doing business?:** 8.9/10 (Category avg: 9.0/10)
- **Data Workflows:** 9.2/10 (Category avg: 8.8/10)
- **Profiling and Classification:** 8.5/10 (Category avg: 8.5/10)
- **Data Joining:** 9.1/10 (Category avg: 8.9/10)


**Seller Details:**

- **Seller:** [Alteryx](https://www.g2.com/sellers/alteryx)
- **Company Website:** https://www.alteryx.com
- **Year Founded:** 1997
- **HQ Location:** Irvine, CA
- **Twitter:** @alteryx (26,220 Twitter followers)
- **LinkedIn® Page:** https://www.linkedin.com/company/903031/ (2,268 employees on LinkedIn®)

**Reviewer Demographics:**
  - **Who Uses This:** Data Analyst, Analyst
  - **Top Industries:** Financial Services, Accounting
  - **Company Size:** 62% Enterprise, 22% Mid-Market


#### Pros & Cons

**Pros:**

- Ease of Use (333 reviews)
- Automation (148 reviews)
- Intuitive (132 reviews)
- Easy Learning (102 reviews)
- Efficiency (102 reviews)

**Cons:**

- Expensive (88 reviews)
- Learning Curve (80 reviews)
- Missing Features (62 reviews)
- Learning Difficulty (55 reviews)
- Slow Performance (41 reviews)

  ### 3. [SAS Viya](https://www.g2.com/products/sas-sas-viya/reviews)
  SAS Viya is a cloud-native data and AI platform that enables teams to build, deploy and scale explainable AI that drives trusted, confident decisions. It unites the entire data and AI life cycle and empowers teams to innovate quickly while balancing speed, automation and governance by design. Viya unifies data management, advanced analytics and decisioning in a single platform, so organizations can move from experimentation to production with confidence, delivering measurable business impact that is secure, explainable and scalable across any environment. Key capabilities required to deliver trusted decisions include: • End-to-end clarity across the data and AI life cycle, with built-in lineage, auditability and continuous monitoring to support defensible decisions. • Governance by design, enabling consistent oversight across data, models and decisions to reduce risk and accelerate adoption. • Explainable AI at scale, so insights and outcomes can be understood, validated and trusted by business and regulators alike. • Operationalized analytics, ensuring value continues beyond deployment through monitoring, retraining and life cycle management. • Flexible, cloud-native deployment, allowing organizations to start anywhere and scale everywhere while maintaining control.


  **Average Rating:** 4.3/5.0
  **Total Reviews:** 707

**User Satisfaction Scores:**

- **Has the product been a good partner in doing business?:** 8.3/10 (Category avg: 9.0/10)
- **Data Workflows:** 8.5/10 (Category avg: 8.8/10)
- **Profiling and Classification:** 8.5/10 (Category avg: 8.5/10)
- **Data Joining:** 8.8/10 (Category avg: 8.9/10)


**Seller Details:**

- **Seller:** [SAS Institute Inc.](https://www.g2.com/sellers/sas-institute-inc-df6dde22-a5e5-4913-8b21-4fa0c6c5c7c2)
- **Company Website:** https://www.sas.com/
- **Year Founded:** 1976
- **HQ Location:** Cary, NC
- **Twitter:** @SASsoftware (60,996 Twitter followers)
- **LinkedIn® Page:** https://www.linkedin.com/company/1491/ (18,238 employees on LinkedIn®)

**Reviewer Demographics:**
  - **Who Uses This:** Student, Statistical Programmer
  - **Top Industries:** Pharmaceuticals, Computer Software
  - **Company Size:** 33% Small-Business, 32% Enterprise


#### Pros & Cons

**Pros:**

- Ease of Use (316 reviews)
- Features (218 reviews)
- Analytics (196 reviews)
- Data Analysis (166 reviews)
- User Interface (147 reviews)

**Cons:**

- Learning Difficulty (151 reviews)
- Learning Curve (144 reviews)
- Complexity (143 reviews)
- Difficult Learning (117 reviews)
- Expensive (108 reviews)

  ### 4. [Domo](https://www.g2.com/products/domo/reviews)
  Domo's AI and Data Products Platform empowers organizations to turn data into actionable insights and solutions. It allows users to seamlessly connect diverse data sources, prepare data for use, and generate dynamic reports and visualizations—all within a single interface. With built-in AI and automation capabilities, teams can easily build and use AI agents, streamline workflows, and create tailored solutions.


  **Average Rating:** 4.3/5.0
  **Total Reviews:** 983

**User Satisfaction Scores:**

- **Has the product been a good partner in doing business?:** 8.8/10 (Category avg: 9.0/10)
- **Data Workflows:** 8.1/10 (Category avg: 8.8/10)
- **Profiling and Classification:** 7.6/10 (Category avg: 8.5/10)
- **Data Joining:** 8.9/10 (Category avg: 8.9/10)


**Seller Details:**

- **Seller:** [Domo](https://www.g2.com/sellers/domo)
- **Company Website:** https://www.domo.com
- **Year Founded:** 2010
- **HQ Location:** American Fork, UT
- **Twitter:** @Domotalk (63,711 Twitter followers)
- **LinkedIn® Page:** https://www.linkedin.com/company/25237/ (1,334 employees on LinkedIn®)

**Reviewer Demographics:**
  - **Who Uses This:** Data Analyst, Business Analyst
  - **Top Industries:** Computer Software, Marketing and Advertising
  - **Company Size:** 49% Mid-Market, 29% Enterprise


#### Pros & Cons

**Pros:**

- Ease of Use (248 reviews)
- Data Visualization (116 reviews)
- Intuitive (95 reviews)
- Easy Integrations (93 reviews)
- Integrations (88 reviews)

**Cons:**

- Learning Curve (66 reviews)
- Missing Features (59 reviews)
- Data Management Issues (55 reviews)
- Expensive (45 reviews)
- Complexity (43 reviews)

  ### 5. [AWS Glue](https://www.g2.com/products/aws-glue/reviews)
  AWS Glue is a serverless data integration service that makes it easier for analytics users to discover, prepare, move, and integrate data from multiple sources for analytics, machine learning, and application develop-ment. You can discover and connect to 70+ diverse data sources, manage your data in a centralized data catalog, and visually create, run, and monitor ETL pipelines to load data into your data lakes. You can im-mediately search and query catalogued data using Amazon Athena, Amazon EMR, and Amazon Redshift Spectrum.


  **Average Rating:** 4.3/5.0
  **Total Reviews:** 191

**User Satisfaction Scores:**

- **Has the product been a good partner in doing business?:** 8.8/10 (Category avg: 9.0/10)
- **Data Workflows:** 8.4/10 (Category avg: 8.8/10)
- **Profiling and Classification:** 8.4/10 (Category avg: 8.5/10)
- **Data Joining:** 8.8/10 (Category avg: 8.9/10)


**Seller Details:**

- **Seller:** [Amazon Web Services (AWS)](https://www.g2.com/sellers/amazon-web-services-aws-3e93cc28-2e9b-4961-b258-c6ce0feec7dd)
- **Year Founded:** 2006
- **HQ Location:** Seattle, WA
- **Twitter:** @awscloud (2,223,984 Twitter followers)
- **LinkedIn® Page:** https://www.linkedin.com/company/amazon-web-services/ (156,424 employees on LinkedIn®)
- **Ownership:** NASDAQ: AMZN

**Reviewer Demographics:**
  - **Who Uses This:** Data Engineer, Software Engineer
  - **Top Industries:** Information Technology and Services, Computer Software
  - **Company Size:** 48% Enterprise, 29% Mid-Market


#### Pros & Cons

**Pros:**

- Ease of Use (6 reviews)
- Data Integration (3 reviews)
- ETL Solutions (3 reviews)
- Features (3 reviews)
- Simple (3 reviews)

**Cons:**

- Slow Performance (3 reviews)
- Debugging Difficulty (2 reviews)
- Difficult Debugging (2 reviews)
- Performance Issues (2 reviews)
- Time-Consuming (2 reviews)

  ### 6. [Visier](https://www.g2.com/products/visier/reviews)
  Visier gives organizations a Workforce AI Edge: a set of AI-powered capabilities that help leaders understand the relationship between people and work, elevate employee productivity, and win by adapting to change faster. The company is the global leader in AI-powered people analytics, workforce planning, and compensation allocation. All Visier technology is underpinned by its Real-time People Data Platform, which uses AI to unlock the business-transforming potential of people data, work data, and the fusion of both. Founded in 2010 by the pioneers of business intelligence, Visier has over 60,000 customers in 75 countries—including enterprises like BASF, Panasonic, Experian, Amgen, eBay, Ford Motor Company, and more. To learn more about Visier, visit www.visier.com.


  **Average Rating:** 4.6/5.0
  **Total Reviews:** 219

**User Satisfaction Scores:**

- **Has the product been a good partner in doing business?:** 9.1/10 (Category avg: 9.0/10)
- **Data Workflows:** 8.1/10 (Category avg: 8.8/10)
- **Profiling and Classification:** 7.9/10 (Category avg: 8.5/10)
- **Data Joining:** 7.7/10 (Category avg: 8.9/10)


**Seller Details:**

- **Seller:** [Visier](https://www.g2.com/sellers/visier-8c589666-edc0-409b-b9fb-0df31e55c335)
- **Year Founded:** 2010
- **HQ Location:** Vancouver, British Columbia
- **Twitter:** @visier (6,182 Twitter followers)
- **LinkedIn® Page:** https://www.linkedin.com/company/visier-analytics/ (566 employees on LinkedIn®)

**Reviewer Demographics:**
  - **Top Industries:** Hospital & Health Care, Information Technology and Services
  - **Company Size:** 82% Enterprise, 17% Mid-Market


#### Pros & Cons

**Pros:**

- Ease of Use (25 reviews)
- Data Analysis (22 reviews)
- Insights (19 reviews)
- Data Visualization (18 reviews)
- Time-saving (18 reviews)

**Cons:**

- Learning Difficulty (12 reviews)
- Expensive (11 reviews)
- Learning Curve (8 reviews)
- Complexity (7 reviews)
- Limited Customization (7 reviews)

  ### 7. [Qlik Sense](https://www.g2.com/products/qlik-sense/reviews)
  Qlik Sense empowers people to make better data-driven decisions and take action. The solution provides augmented analytics for every business need from visualization and dashboards to natural language analytics, custom and embedded analytics, reporting and alerting. Our unique associative technology enhances human intuition with AI-powered insights, offering unmatched capabilities for combining data and exploring information. It indexes the associations in your data, and exposes related and unrelated values as you click, revealing hidden insights that would be missed by query-based tools. And it performs calculations as fast as you can think. Qlik Sense helps users move from passive to active analytics for real-time collaboration and action. And you get robust data integration, application automation and the convenience of SaaS with hybrid multi-cloud capabilities. See why we’ve been named a Gartner Magic Quadrant Leader for Analytics and BI platforms for 11 years in a row. Visit us at [https://www.qlik.com/us/](-	https://www.qlik.com/us/products/qlik-sense?utm_medium=referral&utm_source=G2&utm_team=DIG&utm_term=QlikSense&utm_mpt_id=CKMP5D)


  **Average Rating:** 4.4/5.0
  **Total Reviews:** 759

**User Satisfaction Scores:**

- **Has the product been a good partner in doing business?:** 8.5/10 (Category avg: 9.0/10)
- **Data Joining:** 10.0/10 (Category avg: 8.9/10)


**Seller Details:**

- **Seller:** [Qlik](https://www.g2.com/sellers/qlik)
- **Year Founded:** 1993
- **HQ Location:** Radnor, PA
- **Twitter:** @qlik (64,285 Twitter followers)
- **LinkedIn® Page:** https://www.linkedin.com/company/10162/ (4,529 employees on LinkedIn®)
- **Phone:** 1 (888) 994-9854

**Reviewer Demographics:**
  - **Who Uses This:** Consultant, Data Analyst
  - **Top Industries:** Information Technology and Services, Computer Software
  - **Company Size:** 41% Enterprise, 41% Mid-Market


#### Pros & Cons

**Pros:**

- Ease of Use (55 reviews)
- Data Visualization (31 reviews)
- Analytics (28 reviews)
- Insights Discovery (24 reviews)
- Features (22 reviews)

**Cons:**

- Limited Features (17 reviews)
- Missing Features (16 reviews)
- Expensive (14 reviews)
- Data Management (13 reviews)
- Learning Curve (13 reviews)

  ### 8. [DemandTools](https://www.g2.com/products/demandtools/reviews)
  DemandTools is the secure data quality platform that ensures your data remains your most valuable asset. With DemandTools, you manage your CRM data in minutes, not months, so you always have accurate, report-ready data enabling everyone to do their job more effectively, efficiently, and profitably. By fixing common data problems, automating data quality routines, and working within your specific processes and customizations, DemandTools gives stakeholders accurate insights and reporting, improves business efficiency, and gets you clean data faster, with less effort. DemandTools has 12 modules making it the most versatile and adaptable data quality solution for CRM. Data Quality Assessment Understand how strong or weak your data is and know where to focus remediation efforts. Module: Assess Duplicate Management Detect, eliminate, and prevent duplicate records from misleading your sales and marketing teams and causing friction in your customer journey. Modules: Dedupe, Convert, DupeBlocker, Match Data Migration Management Maintain data integrity while moving data into and out of Salesforce. Modules: Import, Export, Delete, Match Standardization, mass modification, and business insights. Apply record changes en masse and standardize data to get trustworthy insights in every report. Modules: Modify, Tune, Reassign Email Verification Verify email addresses in CRM to keep communication flowing with your customers. Module: Verify Get clean data and strengthen your business with DemandTools.


  **Average Rating:** 4.6/5.0
  **Total Reviews:** 275

**User Satisfaction Scores:**

- **Has the product been a good partner in doing business?:** 8.9/10 (Category avg: 9.0/10)
- **Data Workflows:** 9.1/10 (Category avg: 8.8/10)
- **Profiling and Classification:** 8.8/10 (Category avg: 8.5/10)
- **Data Joining:** 9.2/10 (Category avg: 8.9/10)


**Seller Details:**

- **Seller:** [Validity Inc](https://www.g2.com/sellers/validity-inc)
- **Company Website:** https://www.validity.com
- **Year Founded:** 2018
- **HQ Location:** Boston, Massachusetts
- **Twitter:** @TrustValidity (1,153 Twitter followers)
- **LinkedIn® Page:** https://www.linkedin.com/company/11679353/ (344 employees on LinkedIn®)

**Reviewer Demographics:**
  - **Who Uses This:** Salesforce Administrator
  - **Top Industries:** Computer Software, Information Technology and Services
  - **Company Size:** 48% Mid-Market, 33% Enterprise


#### Pros & Cons

**Pros:**

- Ease of Use (14 reviews)
- Duplicate Management (8 reviews)
- Time-saving (8 reviews)
- Efficiency (5 reviews)
- Salesforce Integration (5 reviews)

**Cons:**

- Limited Functionality (3 reviews)
- Missing Features (3 reviews)
- Learning Curve (2 reviews)
- Poor Interface Design (2 reviews)
- Slow Loading (2 reviews)

  ### 9. [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

**User Satisfaction Scores:**

- **Has the product been a good partner in doing business?:** 9.4/10 (Category avg: 9.0/10)
- **Data Workflows:** 8.7/10 (Category avg: 8.8/10)
- **Profiling and Classification:** 8.6/10 (Category avg: 8.5/10)
- **Data Joining:** 8.6/10 (Category avg: 8.9/10)


**Seller Details:**

- **Seller:** [Incorta](https://www.g2.com/sellers/incorta)
- **Company Website:** https://www.incorta.com/
- **Year Founded:** 2013
- **HQ Location:** San Mateo, CA
- **LinkedIn® Page:** https://www.linkedin.com/company/incorta/ (325 employees on LinkedIn®)

**Reviewer Demographics:**
  - **Top Industries:** Information Technology and Services, Computer Software
  - **Company Size:** 56% Enterprise, 29% Mid-Market


#### Pros & Cons

**Pros:**

- Data Integration (1 reviews)
- Easy Integrations (1 reviews)
- Integrations (1 reviews)

**Cons:**

- Bugs (1 reviews)

  ### 10. [IBM Watson Studio](https://www.g2.com/products/ibm-watson-studio/reviews)
  IBM Watson Studio on IBM Cloud Pak for Data is a leading data science and machine learning solution that helps enterprises accelerate AI-powered digital transformation. It allows businesses to scale trustworthy AI and optimize decisions. Build, run, and manage AI models on any cloud through an automated end-to-end AI lifecycle--simplifying experimentation and deployment, speeding up data exploration and preparation, and improving model development and training. Govern and monitor models to mitigate drift and bias, and manage model risk. Build a ModelOps practice that synchronizes application and model pipelines to operationalize responsible, explainable AI across your enterprise. As a key offering of IBM Cloud Pak for Data, a unified data and AI platform, Watson Studio integrates seamlessly with data management services, data privacy and security capabilities, AI application tooling, open source frameworks, and a robust technology ecosystem. It unites teams and empowers businesses to build the modern information architecture that AI requires and infuse it across the organization. IBM Watson Studio is code-optional, allowing both data scientists and business analysts to work on the same platform by providing the best of open source tools along with visual, drag-and-drop capabilities. It enables organizations to tap into data assets and inject predictions into business processes and modern applications—helping them maximize their business value. It's suited for hybrid multicloud environments that demand mission-critical performance, security, and governance. Features include: • AutoAI that eliminates time-consuming, repetitive tasks by automating data preparation, model development, feature engineering and hyperparameter optimization. • Text Analytics for uncovering insights from unstructured data • Drag-and-drop visual model-building with SPSS Modeler • Broad data access – flat files, spreadsheets, major relational databases • Sophisticated graphics engine for building stunning visualizations • Support for Python 3 Notebooks Watson Studio is available via several deployment options: • IBM Cloud Pak for Data – An open, extensible data and AI platform that runs on any cloud • IBM Cloud Pak for Data System – A hybrid cloud, on-premises platform-in-a-box • IBM Cloud Pak for Data as a Service – A set of IBM Cloud Pak for Data platform services fully managed on the IBM Cloud


  **Average Rating:** 4.2/5.0
  **Total Reviews:** 160

**User Satisfaction Scores:**

- **Has the product been a good partner in doing business?:** 8.0/10 (Category avg: 9.0/10)
- **Data Workflows:** 9.2/10 (Category avg: 8.8/10)
- **Profiling and Classification:** 9.0/10 (Category avg: 8.5/10)
- **Data Joining:** 9.1/10 (Category avg: 8.9/10)


**Seller Details:**

- **Seller:** [IBM](https://www.g2.com/sellers/ibm)
- **Year Founded:** 1911
- **HQ Location:** Armonk, NY
- **Twitter:** @IBM (709,023 Twitter followers)
- **LinkedIn® Page:** https://www.linkedin.com/company/1009/ (324,553 employees on LinkedIn®)
- **Ownership:** SWX:IBM

**Reviewer Demographics:**
  - **Who Uses This:** Software Engineer, CEO
  - **Top Industries:** Information Technology and Services, Computer Software
  - **Company Size:** 50% Enterprise, 30% Small-Business


#### Pros & Cons

**Pros:**

- AI Capabilities (4 reviews)
- AI Technology (4 reviews)
- Ease of Use (4 reviews)
- Machine Learning (4 reviews)
- AI Integration (3 reviews)

**Cons:**

- Expensive (3 reviews)
- Learning Curve (3 reviews)
- Steep Learning Curve (3 reviews)
- Complex Interface (1 reviews)
- Complexity (1 reviews)

  ### 11. [dbt](https://www.g2.com/products/dbt/reviews)
  dbt is a transformation workflow that lets data teams quickly and collaboratively deploy analytics code following software engineering best practices like modularity, portability, CI/CD, and documentation. Now anyone who knows SQL can build production-grade data pipelines.


  **Average Rating:** 4.7/5.0
  **Total Reviews:** 199

**User Satisfaction Scores:**

- **Has the product been a good partner in doing business?:** 8.6/10 (Category avg: 9.0/10)
- **Data Workflows:** 9.1/10 (Category avg: 8.8/10)
- **Profiling and Classification:** 8.3/10 (Category avg: 8.5/10)
- **Data Joining:** 9.1/10 (Category avg: 8.9/10)


**Seller Details:**

- **Seller:** [Fivetran](https://www.g2.com/sellers/fivetran)
- **Year Founded:** 2012
- **HQ Location:** Oakland, CA
- **Twitter:** @fivetran (5,735 Twitter followers)
- **LinkedIn® Page:** https://www.linkedin.com/company/fivetran/ (1,738 employees on LinkedIn®)

**Reviewer Demographics:**
  - **Who Uses This:** Analytics Engineer, Data Engineer
  - **Top Industries:** Information Technology and Services, Computer Software
  - **Company Size:** 57% Mid-Market, 28% Small-Business


#### Pros & Cons

**Pros:**

- Ease of Use (38 reviews)
- Features (22 reviews)
- Automation (19 reviews)
- Transformation (17 reviews)
- Integrations (15 reviews)

**Cons:**

- Limited Functionality (14 reviews)
- Dependency Issues (12 reviews)
- Steep Learning Curve (10 reviews)
- Error Handling (9 reviews)
- Error Reporting (9 reviews)

  ### 12. [Alteryx Designer Cloud](https://www.g2.com/products/alteryx-alteryx-designer-cloud/reviews)
  Designer Cloud powered by Trifacta is part of the Alteryx Analytics Cloud platform. Designer Cloud democratizes data analytics across the organization with an open and interactive cloud platform for anyone who works with data to collaboratively profile, prepare, and pipeline data for analytics and machine learning. Organizations can connect to any data source, across all major cloud data platforms, and integrate Alteryx Analytics Cloud seamlessly into the existing data stack. Designer Cloud provides an interactive, visual user experience with AI/ML-based suggestions to guide users through the exploration and transformation of any dataset.


  **Average Rating:** 4.4/5.0
  **Total Reviews:** 151

**User Satisfaction Scores:**

- **Has the product been a good partner in doing business?:** 8.8/10 (Category avg: 9.0/10)
- **Data Workflows:** 8.6/10 (Category avg: 8.8/10)
- **Profiling and Classification:** 8.4/10 (Category avg: 8.5/10)
- **Data Joining:** 8.8/10 (Category avg: 8.9/10)


**Seller Details:**

- **Seller:** [Alteryx](https://www.g2.com/sellers/alteryx)
- **Year Founded:** 1997
- **HQ Location:** Irvine, CA
- **Twitter:** @alteryx (26,220 Twitter followers)
- **LinkedIn® Page:** https://www.linkedin.com/company/903031/ (2,268 employees on LinkedIn®)
- **Ownership:** Private

**Reviewer Demographics:**
  - **Top Industries:** Information Technology and Services, Hospital & Health Care
  - **Company Size:** 35% Enterprise, 35% Small-Business


  ### 13. [SAS Data Management](https://www.g2.com/products/sas-data-management/reviews)
  SAS Data Management is a comprehensive solution designed to transform raw data into a valuable business asset by improving, integrating, managing, and governing data across an organization. It enables users to access data from various sources, create rules, collaborate with teams, and manage metadata, thereby preparing data for analytics and informed decision-making. Key Features and Functionality: - Data Access and Integration: Seamlessly access data from diverse sources, including legacy systems and modern platforms like Hadoop, ensuring comprehensive data integration. - Data Quality and Cleansing: Utilize embedded tools to automatically identify and rectify data quality issues, reducing errors and inconsistencies. - Data Preparation: Prepare data for analytics and reporting in a self-service environment without the need for coding or IT assistance, enhancing productivity. - Data Governance: Implement consistent policies and processes to ensure data conforms to established standards and regulatory requirements. - Personal Data Protection: Identify and monitor personal data sources to comply with privacy regulations such as GDPR. - Data Federation and Stewardship: Simplify data integration complexities with a virtual data environment that delivers a complete data picture in a user-friendly format. Primary Value and Solutions Provided: SAS Data Management addresses the critical need for organizations to manage their data effectively, turning it into a strategic asset. By providing a unified platform for data access, integration, quality, governance, and master data management, it eliminates the need for multiple, overlapping tools. This consolidation leads to improved data accuracy, streamlined operations, and enhanced decision-making capabilities. Organizations can ensure that all internal and third-party data remains clean and well-managed, facilitating compliance with regulatory standards and enabling more efficient and effective business processes.


  **Average Rating:** 4.1/5.0
  **Total Reviews:** 96

**User Satisfaction Scores:**

- **Has the product been a good partner in doing business?:** 8.1/10 (Category avg: 9.0/10)
- **Data Workflows:** 9.8/10 (Category avg: 8.8/10)
- **Profiling and Classification:** 9.6/10 (Category avg: 8.5/10)
- **Data Joining:** 9.6/10 (Category avg: 8.9/10)


**Seller Details:**

- **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 (60,996 Twitter followers)
- **LinkedIn® Page:** https://www.linkedin.com/company/1491/ (18,238 employees on LinkedIn®)
- **Phone:** 1-800-727-0025

**Reviewer Demographics:**
  - **Top Industries:** Higher Education, Research
  - **Company Size:** 52% Enterprise, 26% Small-Business


#### Pros & Cons

**Pros:**

- Ease of Use (12 reviews)
- Analytics (5 reviews)
- Data Cleaning (4 reviews)
- Data Quality (4 reviews)
- Data Management (3 reviews)

**Cons:**

- Expensive (7 reviews)
- Not User-Friendly (3 reviews)
- Slow Performance (3 reviews)
- Training Required (3 reviews)
- Complexity (2 reviews)

  ### 14. [OWOX](https://www.g2.com/products/owox/reviews)
  OWOX Data Marts is a Free Forever Self-Service Analytics Platform that brings live, trusted data to spreadsheets and dashboards of decision-makers. Ask in plain English or click to build – your trusted reports update in real time with no analyst in the loop. With OWOX Data Marts, companies grow revenue as fast as they collect new data by enabling self-service reporting for everyone. Trusted by 165,000+ users in data teams, but also in marketing, finance, and product teams: from fast-scaling startups to global enterprises, OWOX products powers decisions across every department with data people actually trust. ‍ Self-hosted and Cloud Deployment are available to suit any data stack. Imagine a world where exploring data is as easy as driving a car, without the limitations of public transport (traditional BI dashboards) or the cost of a private driver (data analysts). That's exactly what we assure you!


  **Average Rating:** 4.9/5.0
  **Total Reviews:** 290

**User Satisfaction Scores:**

- **Has the product been a good partner in doing business?:** 9.4/10 (Category avg: 9.0/10)


**Seller Details:**

- **Seller:** [OWOX](https://www.g2.com/sellers/owox)
- **Year Founded:** 2002
- **HQ Location:** WALNUT, California
- **Twitter:** @owox (434 Twitter followers)
- **LinkedIn® Page:** https://www.linkedin.com/company/1721152/ (67 employees on LinkedIn®)

**Reviewer Demographics:**
  - **Who Uses This:** Chief Marketing Officer, CEO
  - **Top Industries:** Marketing and Advertising, Information Technology and Services
  - **Company Size:** 48% Small-Business, 43% Mid-Market


#### Pros & Cons

**Pros:**

- Ease of Use (21 reviews)
- Helpful (15 reviews)
- Data Management (14 reviews)
- Customer Support (13 reviews)
- Analytics (7 reviews)

**Cons:**

- Data Management Issues (4 reviews)
- Error Handling (3 reviews)
- Expensive (2 reviews)
- Integration Issues (2 reviews)
- Lack of Information (2 reviews)

  ### 15. [TIMi](https://www.g2.com/products/timi/reviews)
  TIMi is the most efficient Data Science and Data Processing Platform. Since 2007, we have been creating and improving the most powerful framework to push the barriers of analytics, predictive analytics, AI and Big Data, while offering a helpful, fast and friendly environment. The TIMi Suite consists of four tools: 1. Anatella (Analytical ETL, Data Prep & Big Data), 2. Modeler (Auto-ML / Automated Predictive Modelling / Automated-AI), 3. StarDust (3D Segmentation) 4. Kibella (BI Dashboarding solution). TIMi dominates the Data Science market: In the "Summer 2022 - Momentum Report” from G2, in the “Data Science” category, TIMi has the #1 rank: TIMi is the Data Science solution with both the highest market growth and the highest customer-satisfaction! More about this subject here: https://timi.eu/blog/timi-the-number-one-data-science-platform/


  **Average Rating:** 4.8/5.0
  **Total Reviews:** 67

**User Satisfaction Scores:**

- **Has the product been a good partner in doing business?:** 9.3/10 (Category avg: 9.0/10)
- **Data Workflows:** 9.2/10 (Category avg: 8.8/10)
- **Profiling and Classification:** 8.8/10 (Category avg: 8.5/10)
- **Data Joining:** 9.4/10 (Category avg: 8.9/10)


**Seller Details:**

- **Seller:** [TIMi SPRL](https://www.g2.com/sellers/timi-sprl)
- **Company Website:** https://timi.eu
- **Year Founded:** 2007
- **HQ Location:** Brussels
- **Twitter:** @TIMiSuite (3,546 Twitter followers)
- **LinkedIn® Page:** https://www.linkedin.com/company/timisuite/ (87 employees on LinkedIn®)

**Reviewer Demographics:**
  - **Top Industries:** Information Technology and Services, Banking
  - **Company Size:** 38% Small-Business, 33% Enterprise


#### Pros & Cons

**Pros:**

- Ease of Use (3 reviews)
- Automation (2 reviews)
- Customer Support (2 reviews)
- Efficiency (2 reviews)
- Features (2 reviews)

**Cons:**

- Difficult Customization (1 reviews)
- Difficult Setup (1 reviews)
- Implementation Difficulty (1 reviews)
- Integration Difficulty (1 reviews)
- Integration Issues (1 reviews)

  ### 16. [Altair Monarch](https://www.g2.com/products/altair-monarch/reviews)
  An industry leader with over 30 years of experience in data discovery and transformation, Altair Monarch offers the fastest and easiest way to extract data from any source. Simple to construct workflows that require no coding enable users to collaborate as they transform difficult data such as PDFs spreadsheets, text files, as well as from big data and other structured sources, into rows and columns. Whether data is on premises or in the cloud, Altair can automate preparation tasks for expedited results and deliver data you trust for smart business decision making. To learn more about Altair Monarch or download a free version of its enterprise software, please click the links below.


  **Average Rating:** 4.5/5.0
  **Total Reviews:** 91

**User Satisfaction Scores:**

- **Has the product been a good partner in doing business?:** 8.4/10 (Category avg: 9.0/10)
- **Data Workflows:** 9.2/10 (Category avg: 8.8/10)
- **Profiling and Classification:** 9.0/10 (Category avg: 8.5/10)
- **Data Joining:** 9.1/10 (Category avg: 8.9/10)


**Seller Details:**

- **Seller:** [Altair](https://www.g2.com/sellers/altair-186799f5-3238-493f-b3ad-b8cac484afd7)
- **Year Founded:** 1985
- **HQ Location:** Troy, MI
- **LinkedIn® Page:** https://www.linkedin.com/company/8323/ (3,169 employees on LinkedIn®)
- **Ownership:** NASDAQ:ALTR
- **Total Revenue (USD mm):** $458

**Reviewer Demographics:**
  - **Top Industries:** Financial Services, Hospital & Health Care
  - **Company Size:** 54% Enterprise, 27% Mid-Market


  ### 17. [Savant Labs](https://www.g2.com/products/savant-labs/reviews)
  Savant is an AI 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 workflows, so teams can be more efficient without sacrificing accuracy, control, or compliance. 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 is built in, not bolted on: Audit trail, data lineage, SOX controls, and role-based access 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 data automation: Automate any data task end to end — prep, blending, transformation, publishing, and alerting. Works with structured and unstructured data, including PDFs, scanned documents, and ERP extracts. - Deterministic workflow engine: 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 and data lineage: 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. - User-friendly interface: No SQL, no code, no IT tickets. If your team can use Excel, they can build and run workflows in Savant. - 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:** 4.6/5.0
  **Total Reviews:** 38

**User Satisfaction Scores:**

- **Has the product been a good partner in doing business?:** 9.8/10 (Category avg: 9.0/10)
- **Data Workflows:** 9.3/10 (Category avg: 8.8/10)
- **Profiling and Classification:** 7.9/10 (Category avg: 8.5/10)
- **Data Joining:** 9.4/10 (Category avg: 8.9/10)


**Seller Details:**

- **Seller:** [Savant Labs](https://www.g2.com/sellers/savant-labs)
- **Company Website:** https://www.savantlabs.io
- **Year Founded:** 2021
- **HQ Location:** San Francisco, California
- **LinkedIn® Page:** https://www.linkedin.com/company/savant-labs (62 employees on LinkedIn®)

**Reviewer Demographics:**
  - **Top Industries:** Computer Software, Logistics and Supply Chain
  - **Company Size:** 46% Mid-Market, 31% Enterprise


#### Pros & Cons

**Pros:**

- Ease of Use (14 reviews)
- Customer Support (9 reviews)
- User Interface (7 reviews)
- Integrations (6 reviews)
- Scalability (6 reviews)

**Cons:**

- Learning Curve (7 reviews)
- Learning Difficulty (6 reviews)
- Integration Issues (3 reviews)
- Access Issues (2 reviews)
- Data Management (2 reviews)

  ### 18. [Prophecy](https://www.g2.com/products/prophecy-prophecy/reviews)
  Prophecy is the AI data prep and analysis platform. We make business data teams incredibly productive with AI agentic coworkers. Prophecy introduces an AI-powered data lifecycle — generate, refine, deploy — where AI agents and data teams collaborate across text, visual, and code interfaces to move faster, automate repetitive tasks, and ship trusted pipelines to production.


  **Average Rating:** 4.7/5.0
  **Total Reviews:** 30

**User Satisfaction Scores:**

- **Has the product been a good partner in doing business?:** 9.3/10 (Category avg: 9.0/10)


**Seller Details:**

- **Seller:** [Prophecy](https://www.g2.com/sellers/prophecy)
- **Year Founded:** 2017
- **HQ Location:** San Diego, US
- **Twitter:** @Prophecy_io (315 Twitter followers)
- **LinkedIn® Page:** https://www.linkedin.com/company/prophecy-io/ (183 employees on LinkedIn®)

**Reviewer Demographics:**
  - **Who Uses This:** Senior Data Engineer
  - **Top Industries:** Financial Services, Insurance
  - **Company Size:** 70% Enterprise, 17% Mid-Market


#### Pros & Cons

**Pros:**

- Ease of Use (1 reviews)
- Integration (1 reviews)
- Intuitive (1 reviews)
- Speed (1 reviews)

**Cons:**

- Not User-Friendly (2 reviews)
- Complex UI (1 reviews)
- Difficulty (1 reviews)
- Feature Limitations (1 reviews)
- High Complexity (1 reviews)

  ### 19. [Toad Data Point](https://www.g2.com/products/toad-data-point/reviews)
  Seamlessly access more than 50 data sources both on premises and in the cloud and switch between these data sources with near-zero transition times. Connect, query and prepare data for faster business insights. Easy data profiling and cleansing, simplified data federation slashes up to 50 percent of your time to routine data delivery and enables you to take a huge leap in being more data driven.


  **Average Rating:** 4.0/5.0
  **Total Reviews:** 21

**User Satisfaction Scores:**

- **Has the product been a good partner in doing business?:** 7.1/10 (Category avg: 9.0/10)


**Seller Details:**

- **Seller:** [Quest Software](https://www.g2.com/sellers/quest-software)
- **Year Founded:** 1987
- **HQ Location:** Austin, TX
- **Twitter:** @Quest (17,156 Twitter followers)
- **LinkedIn® Page:** https://www.linkedin.com/company/2880/ (3,594 employees on LinkedIn®)
- **Ownership:** NYSE: DGX

**Reviewer Demographics:**
  - **Company Size:** 62% Enterprise, 33% Mid-Market


  ### 20. [Datameer](https://www.g2.com/products/datameer/reviews)
  Datameer revolutionizes data transformation with a low-code approach, trusted by top global enterprises. Craft, transform, and publish data seamlessly with no code and SQL, simplifying complex data engineering tasks. Empower your data teams to make informed decisions confidently while saving costs and ensuring responsible self-service analytics.


  **Average Rating:** 4.2/5.0
  **Total Reviews:** 24

**User Satisfaction Scores:**

- **Has the product been a good partner in doing business?:** 8.5/10 (Category avg: 9.0/10)
- **Data Workflows:** 7.7/10 (Category avg: 8.8/10)
- **Profiling and Classification:** 8.3/10 (Category avg: 8.5/10)
- **Data Joining:** 9.0/10 (Category avg: 8.9/10)


**Seller Details:**

- **Seller:** [Datameer](https://www.g2.com/sellers/datameer)
- **Year Founded:** 2009
- **HQ Location:** San Francisco, CA
- **Twitter:** @datameer (11,236 Twitter followers)
- **LinkedIn® Page:** https://www.linkedin.com/company/972396/ (165 employees on LinkedIn®)

**Reviewer Demographics:**
  - **Top Industries:** Information Technology and Services
  - **Company Size:** 63% Enterprise, 21% Mid-Market


  ### 21. [Coginiti](https://www.g2.com/products/coginiti/reviews)
  Coginiti is a SQL-first collaborative data operations platform that empowers teams to build, publish, and consume quality data products, streamlining the data analytics lifecycle from inception to insights. Integrating with the widest variety of data platforms and tools, Coginiti enables analysts, engineers, and data scientists to collaborate in real-time, breaking down silos and fostering innovation. Its intuitive interface simplifies managing complex data workflows, ensuring governance and consistency across projects. Key Features: - Realtime Collaboration - Flexible Data Modeling - Data Quality Testing - Visualize Data Lineage - Native Scheduling - Powerful APIs - AI Assistant Coginiti facilitates a seamless transition from data preparation to actionable intelligence. It’s not just about refining your data strategy or scaling your analytics capabilities; it’s about empowering your organization to harness the full potential of data for informed decision-making. Discover the power of Coginiti and transform your data operations. Coginiti offers products for individual analysts, data teams, and enterprises.


  **Average Rating:** 4.5/5.0
  **Total Reviews:** 29

**User Satisfaction Scores:**

- **Has the product been a good partner in doing business?:** 8.3/10 (Category avg: 9.0/10)


**Seller Details:**

- **Seller:** [Coginiti Corp](https://www.g2.com/sellers/coginiti-corp)
- **Year Founded:** 2020
- **HQ Location:** Atlanta , GA
- **Twitter:** @coginiti (70 Twitter followers)
- **LinkedIn® Page:** https://www.linkedin.com/company/coginiti (33 employees on LinkedIn®)

**Reviewer Demographics:**
  - **Company Size:** 66% Enterprise, 28% Mid-Market


  ### 22. [IBM Databand](https://www.g2.com/products/ibm-databand/reviews)
  Detect and resolve your data issues faster than ever with Databand. The only continuous data observability platform that catches bad data before it impacts your business. Book a demo today --\> https://www.ibm.com/account/reg/us-en/signup?formid=DEMO-dataaidataband CORE CAPABILITIES Incident Management Improve data reliability and quality under one roof with a single pane of glass for all your data incidents. Data Reliability Monitoring Monitor data pipeline errors such as failed runs, longer than expected durations, missing data operations, and unexpected schema changes. Data Quality Metrics Continuously validate data quality with dataset metrics for SLAs, column changes, and null records. Anomaly Detection Eliminate the unknown by seeing trends & detecting anomalies from your metadata in real time. DataOps Alerting and Routing Customize incident alerts and route notifications to impacted DataOps teams for faster resolution. End-to-end Lineage Visualize how data incidents impact upstream and downstream components of your data stack. Website www.ibm.com/products/databand


  **Average Rating:** 4.3/5.0
  **Total Reviews:** 65

**User Satisfaction Scores:**

- **Has the product been a good partner in doing business?:** 8.3/10 (Category avg: 9.0/10)
- **Data Workflows:** 8.8/10 (Category avg: 8.8/10)
- **Profiling and Classification:** 8.3/10 (Category avg: 8.5/10)
- **Data Joining:** 8.8/10 (Category avg: 8.9/10)


**Seller Details:**

- **Seller:** [IBM](https://www.g2.com/sellers/ibm)
- **Year Founded:** 1911
- **HQ Location:** Armonk, NY
- **Twitter:** @IBM (709,023 Twitter followers)
- **LinkedIn® Page:** https://www.linkedin.com/company/1009/ (324,553 employees on LinkedIn®)
- **Ownership:** SWX:IBM

**Reviewer Demographics:**
  - **Who Uses This:** Software Engineer, Data Analyst
  - **Top Industries:** Information Technology and Services, Computer Software
  - **Company Size:** 44% Mid-Market, 33% Enterprise


#### Pros & Cons

**Pros:**

- Anomaly Detection (2 reviews)
- Monitoring (2 reviews)
- Automation (1 reviews)
- Dashboard Customization (1 reviews)
- Data Management (1 reviews)

**Cons:**

- Limited Features (3 reviews)
- Expensive (2 reviews)
- Integration Issues (2 reviews)
- Learning Difficulty (2 reviews)
- Missing Features (2 reviews)



## Parent Category

[IT Infrastructure Software](https://www.g2.com/categories/it-infrastructure)



## Related Categories

- [Data Quality Tools](https://www.g2.com/categories/data-quality)
- [Analytics Platforms](https://www.g2.com/categories/analytics-platforms)
- [ETL Tools](https://www.g2.com/categories/etl-tools)



---

## Buyer Guide

### What You Should Know About Data Preparation Software

### What are data preparation tools and software?

The amount of data companies collect is staggering. Even a mid-sized business can quickly generate millions of raw data points about its customers, business, and technology performance. As a company’s analytics multiply, proper data management can become insurmountable for even the most seasoned data prep expert — not to mention companies without a specialist on hand. Data prep tools are designed to rummage through this pile of data and aggregate relevant insights for users. These tools are increasingly valuable and necessary for businesses with an endless influx of large data sets. These tools help draw valuable conclusions about important data points through the noise of excess information.

A popular term for this process is called data wrangling. Data wrangling evokes the full capabilities of these tools. They can mine useful, relevant analytics from an overwhelming stream of different data sources. Modern businesses must make timely, critical decisions in response to the diverse insights generated by these data wrangling tools. These tools compile real-time analytics about product users, sales numbers, system performance, and more. The tools in this emerging space help streamline the data preparation process, gleaning precise information from large data sets. As a business’s data piles up, data prep tools enable users to find important data points with the push of a button. This way, companies can leverage actionable insights immediately without sorting through hours of data.

### Key benefits of using data preparation tools

- Performing comprehensive scans of large data sets from disparate data sources
- Profiling relevant data based on custom workflows and filters
- Blending actionable data from large, distributed sets into a clean, optimized file
- Enabling faster, more accurate analysis of relevant information without the need for manual combing of databases

### Why use data preparation solutions?

In the early days of analytics, a small team would be responsible for manually preparing data — managing quality assurance for an entire company’s database, and pulling together actionable insights. This is still the case for thousands of organizations across multiple industries. As technology advances, the volume of unstructured data has grown immensely. People generate more data than businesses know what to do with, creating a unique and unprecedented challenge for data science experts and executives trying to make sense of the analytics. Data prep technology was created out of this growing necessity, with the ability to pick through massive amounts of unstructured data and present only the data points that matter for a given scenario. This relieves IT specialists of this strenuous task and makes an impossible amount of data more digestible.

In addition to finding, profiling, and combining data based on user specifications, certain solutions in this category assist with data transformation or converting data types into different forms or structures for analysis purposes. This creates a unified view of the most relevant analytics for convenient analysis and eventual exporting into external systems. Just as the amount of data has increased in recent years, so has the variety of data types, formats, and sources. Data preparation platforms work to identify or profile the most valuable data across these various types and deliver it in the most useful way for each new scenario. These advanced tools can save employees time while creating opportunities with previously unattainable data, especially if a business has an extensive portfolio of data sources.

### Who uses data prep tools?

The solutions in this category benefit companies with a substantial pool of data and a complex network of data sources. For smaller companies in certain industries, data prep may still be a manual process that does not require new technology. However, since many organizations utilize various types of software and third-party partnerships, they generate mountains of data on a daily basis. As a result, more and more businesses are eligible for these tools.

The following teams or individuals will most likely use these solutions in a given organization.

**IT specialists —** If a company has an IT department, these employees are the most logical choice for general data and test data preparation. IT specialists already have a comprehensive view of the computer systems and software platforms used across an organization. They may already be the primary owners of analytics tasks such as data enrichment and data cleaning. The analytics platforms featured in this category empower IT specialists to expedite the quality assurance process and create clean data sets for internal use or to be shared across their organization.

**Data analysts and engineers —** As the data realm has swelled in size, tech-forward companies have started to seek designated employees to collect and draw conclusions from company analytics. These data analyst roles are typical in organizational structures and third-party agency settings, such as [data governance services providers](https://www.g2.com/categories/data-governance-services). Whether employed with one of these firms or on a company’s full-time staff, data specialists benefit from one of the tools in this space. In some cases, data prep will be a daily responsibility in this line of work. Pulling various data sets for additional analysis or tests and using the results to influence business outcomes emphasizes the impact this technology can have on a given organization. The correct data prep solution can be an indispensable asset for data engineers, analytics executives, and others with a strong focus on data work.

### Features of data preparation software solutions

The robust tools in this software category offer a diverse range of functionalities related to the process of data preparation. The following are some prominent features of these unique offerings.

**Workflow scheduling and monitoring —** Depending on the intended use of these tools, employees may want to map out an automated query to prepare certain groupings of data regularly. This might involve a custom data flow builder or a similar user interface for customization. Using these tools, administrators can adjust the specific details of each workflow, including analytics filters, which sources to pull from, and the schedule for executing the query. A company may be able to adjust other components of the process, such as validation details and the destination for exporting finished data sets. Dashboards on some tools can help display analytics related to data prep workflows, including general efficiency and results summaries.

As a company creates data prep queries, whether for one-off events or routine workflows, a company may be able to configure the data blending and joining process as it relates to each function. Data blending is another common term used to describe the merging of analytics from separate sets into a cohesive group to draw conclusions and continued analysis. When configuring the intelligent algorithms on these platforms, companies can specify how they want the data joined together and presented, for instance, which data type they prefer and how the data should be ordered. Whether called data preparation, data wrangling, or data blending, the solutions in this category can assist with this increasingly popular business strategy to help bring divergent analytics together for a unified purpose.

**Data profiling —** Once the intended analytics are pulled and organized using these tools, certain platforms can assess the data and help determine the additional purposes it can be used for. This is also known as data profiling. Some tools in this category offer more powerful profiling features than others, allowing for rich analytics and summaries about prepared data sets as they are constructed. If data profiling features are not present, a company might assign certain data analysts or other specialists to profile the finished data sets and determine the best course of action to take as the results are delivered.

### Software and services related to data preparation software

Depending on the value an organization places on data and the scope of an organization’s technology infrastructure, the analytics lifecycle can be complex and demanding. The following solutions go hand in hand with data preparation tools in collecting, studying, and using company data. They can help an organization make data analysis both practical and rewarding.

[**Data visualization software**](https://www.g2.com/categories/data-visualization) **—** Data visualization is the process of turning valuable analytics into visuals that can be studied and shared as needed. Data visualization software lets users import database files and create eye-catching charts and graphs displaying certain findings or data selections in an accessible format. Data preparation platforms often integrate with certain data visualization tools, allowing for prepared data to be quickly and seamlessly converted into dashboards, interactive graphs, or other visual files. Whether a department is presenting company-wide KPIs or complex insights for specific teams or business partners, these solutions are a practical way to make data presentable for others, allowing a company to highlight its findings as desired.

[**Business intelligence software**](https://www.g2.com/categories/business-intelligence) **—** Business intelligence software, or BI software, includes data visualization platforms and related technology for analyzing data and revealing the actionable insights scattered across giant pools of information. BI tools are increasingly essential for companies seeking to shape their business strategy around a steady data flow. Many of the tools in these categories require IT assistance for implementation and connecting disparate sources into a functional analytics architecture. Once this information network is established, businesses can leverage it in several ways, including self-service analytics and embedded analytics within business applications. BI tools can create a sturdy foundation of valuable data from multiple sources to build a data preparation strategy and utilize a solution from the data preparation category.

[**Data warehouse software**](https://www.g2.com/categories/data-warehouse) **—** Data warehouse software provides a reliable storage hub for the collective data generated across an organization, from the sales department to the software testing team. Analytics tools such as data prep software often sync with an internal data warehouse to analyze large data sets without providing separate storage for these large, critical files. A data infrastructure may require several solutions for companies with many moving parts, each with its specific function. Data warehouses provide secure storage for these massive data files as they expand, freeing up other data platforms to perform their respective functions with little interruption.

### How to choose the best data preparation tool

When selecting a data preparation tool, consider a few key factors to ensure it aligns with your unique data needs and organizational resources.

First, assess your data's complexity and your team's technical skill level. Some tools are better suited for advanced technical users with programming knowledge, while others are designed for ease of use, making them accessible to non-technical team members. Look for a tool that strikes the right balance between functionality and usability for your team.

Next, think about performance and scalability. As your data grows, your tool should be able to handle increased volumes without a dip in efficiency. Make sure the tool integrates smoothly with your existing infrastructure, such as cloud storage, data lakes, or on-premises systems, to avoid compatibility issues down the line.

Don’t overlook the specific needs of your data workflows. Consider how often your data is updated and whether you need real-time processing capabilities. Advanced features like data profiling, which helps uncover patterns and quality issues, or specialized data transformation options might be essential for more complex datasets. Evaluate these aspects carefully to ensure the tool meets your immediate and long-term data preparation needs.

By evaluating these factors, you’ll be well on your way to choosing a data preparation tool that meets your current requirements and can scale as your organization grows.




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## Frequently Asked Questions

### How do data preparation tools facilitate collaboration among teams?

Data preparation tools enhance team collaboration by enabling real-time data sharing and version control, which allows multiple users to work on datasets simultaneously. Features like automated workflows and integration with collaboration platforms streamline communication and reduce errors. Tools such as Alteryx, Talend, and Trifacta are noted for their user-friendly interfaces that facilitate cross-departmental collaboration, with users highlighting improved project turnaround times and better alignment on data-driven decisions. Additionally, the ability to document processes within these tools fosters transparency and knowledge sharing among team members.



### How do data preparation tools handle data quality and cleansing?

Data preparation tools typically handle data quality and cleansing through features like automated data profiling, which identifies inconsistencies and errors, and data validation rules that ensure accuracy. For instance, tools like Alteryx and Talend are noted for their robust data cleansing capabilities, allowing users to standardize formats and remove duplicates effectively. Additionally, platforms such as Informatica and Trifacta offer advanced algorithms for anomaly detection and data enrichment, enhancing overall data integrity. User reviews highlight the importance of these features in improving data reliability and usability.



### How do data preparation tools integrate with existing data sources?

Data preparation tools typically integrate with existing data sources through various connectors and APIs, allowing seamless access to databases, cloud storage, and other data repositories. For instance, tools like Alteryx and Talend are noted for their extensive integration capabilities, supporting connections to platforms such as Salesforce, Google Analytics, and SQL databases. Users frequently highlight the ease of integration as a key feature, with many reporting that these tools facilitate real-time data access and transformation, enhancing overall workflow efficiency.



### How do I assess the performance of different data preparation tools?

To assess the performance of different data preparation tools, consider user ratings, feature sets, and customer feedback. For instance, Alteryx leads with a high user satisfaction score of 4.5/5, praised for its intuitive interface and robust analytics capabilities. Talend follows closely with a score of 4.4/5, noted for its strong integration features. Informatica ranks at 4.3/5, valued for its data governance tools. Additionally, look at user reviews highlighting ease of use, support quality, and scalability to make informed comparisons.



### How do I evaluate the scalability of a data preparation solution?

To evaluate the scalability of a data preparation solution, consider user feedback on performance under increasing data loads, integration capabilities with other tools, and support for distributed processing. Products like Alteryx, Talend, and Informatica are noted for their robust scalability features, with users highlighting Alteryx's ability to handle large datasets efficiently and Talend's cloud capabilities for scaling operations. Additionally, Informatica users appreciate its performance in enterprise environments, indicating strong scalability across various use cases.



### How user-friendly are the leading data preparation platforms?

The leading data preparation platforms exhibit varying levels of user-friendliness. For instance, Alteryx is highly rated for its intuitive interface, receiving a user satisfaction score of 8.9/10. Talend also scores well, with users appreciating its ease of use, reflected in a score of 8.5/10. Informatica stands out for its robust features but has a slightly lower user-friendliness rating of 7.8/10. Overall, Alteryx and Talend are considered the most user-friendly options in the market.



### What are common use cases for data preparation in businesses?

Common use cases for data preparation in businesses include data cleaning to ensure accuracy, data transformation for compatibility with analytics tools, and data integration from multiple sources to create a unified view. Users frequently highlight the importance of these processes in enhancing data quality and facilitating better decision-making. Additionally, businesses utilize data preparation for generating reports and dashboards, enabling effective data visualization and insights. Tools like Alteryx, Talend, and Informatica are often mentioned for their capabilities in these areas.



### What are the key features to look for in a data preparation tool?

Key features to look for in a data preparation tool include data integration capabilities, which allow seamless connection to various data sources, and data cleansing functionalities to ensure accuracy and consistency. User-friendly interfaces are crucial for ease of use, while automation features can significantly enhance efficiency. Additionally, robust data transformation options enable users to manipulate data effectively, and strong collaboration tools facilitate teamwork. Security features are also essential to protect sensitive data throughout the preparation process.



### What is the average pricing model for data preparation software?

The average pricing model for data preparation software typically ranges from $10 to $150 per user per month, with some vendors offering tiered pricing based on features and usage. For instance, products like Alteryx and Talend often have subscription-based models, while others may offer one-time licensing fees. Additionally, many solutions provide free trials or freemium options to attract users. Overall, pricing can vary significantly based on the complexity of features and the scale of deployment.



### What security measures should I consider when choosing data preparation software?

When choosing data preparation software, consider security measures such as data encryption, user access controls, and compliance with regulations like GDPR. Products like Alteryx, Talend, and Informatica are noted for robust security features, including role-based access and audit trails. Additionally, look for software that offers secure data transfer protocols and regular security updates, as these are critical for protecting sensitive information. User reviews highlight the importance of these features in ensuring data integrity and compliance.



### What support options are typically available for data preparation software?

Data preparation software typically offers a range of support options, including live chat, email support, and extensive documentation. For instance, products like Alteryx and Talend provide robust customer support with high user satisfaction ratings, often highlighting the effectiveness of their live chat options. Additionally, many platforms offer community forums and knowledge bases, which users find valuable for troubleshooting and learning best practices. Overall, the availability of these support channels significantly enhances user experience and satisfaction.



### What types of data can be processed by data preparation tools?

Data preparation tools can process various types of data, including structured data (like databases and spreadsheets), semi-structured data (such as JSON and XML), and unstructured data (including text, images, and social media content). Users frequently highlight the ability of tools like Alteryx, Talend, and Informatica to handle diverse data formats, enabling comprehensive data cleansing, transformation, and integration. Additionally, many tools support real-time data processing and batch processing, catering to different analytical needs.