Market Perspectives

ISG Buyers Guide for Data Management in 2025 Classifies and Rates Software Providers

Written by ISG Software Research | Oct 22, 2025 12:00:02 PM

ISG Research is happy to share insights gleaned from our latest Buyers Guide, an assessment of how well software providers’ offerings meet buyers’ requirements. The Data Management: ISG Research Buyers Guide is the distillation of a year of market and product research by ISG Research.

Data management combines functionality addressing data governance, data quality, master data management, data integration and data intelligence to ensure that the enterprise is collecting, storing and processing data in accordance with strategic goals and regulatory requirements.

ISG defines data management as the administration of data throughout its lifecycle, from generation to consumption, enabling users to ensure that data is valid and consistent and can be trusted for operational use cases and analytic decision-making.

Data management has been a critical component of enterprise IT strategies for decades, used to ensure that data is clean, well-organized and compliant with regulatory requirements. The elevated expectations and demands associated with artificial intelligence (AI) are a forcing function for enterprises to take long-overdue steps to improve data management, however.

Data is integral to AI. Large volumes of data are required to train models, while data freshness is important to inferencing in interactive applications and data quality is fundamental to ensuring that the output of agentic and generative AI initiatives can be relied upon. Poor data management can, therefore, be an impediment to success with AI. While AI-ready data is clean, well-organized and compliant with regulatory standards, too many enterprises find themselves struggling with data that is fragmented, inconsistent and not easily accessible.

More than one-half (54%) of participants in ISG’s 2025 Market Lens Data and AI Program Study cited the usability of data for AI applications as a significant data challenge. As such, even if enterprises have proven the value of AI with small-scale initiatives, many have identified the need to take one step back by pausing to improve data management with a view to subsequently taking two steps forward with accelerated strategic AI initiatives.

Data integration is a set of processes and technologies that enable enterprises to extract, combine, transform and process data from multiple internal and external data platforms and applications to maximize the value of analytic and operational use. Without data integration, business data would be trapped in the applications and systems in which it was generated. Analysis of individual data sources—customer or product data, for example—can provide insights to improve operational efficiency. However, the combination of data from multiple sources enables enterprises to innovate, improving customer experience and revenue generation, for example, by targeting the most lucrative customers with offers to adopt the latest product.

Data governance enables organizations to ensure data is cataloged, trusted and protected, improving business processes that accelerate analytics initiatives while supporting compliance with data privacy and security policies as well as regulatory requirements. While not all data governance initiatives are driven by regulatory compliance, the risk of falling afoul of privacy (and human rights) laws ensures that regulatory compliance influences data-processing requirements and all data governance projects. Good data governance provides guardrails that enable enterprises to act quickly while protecting the business from risks related to regulatory requirements, data-quality issues and data-reliability concerns.

Maintaining data quality and trust is a perennial data-management challenge, often preventing enterprises from operating at the speed of business. As enterprises aspire to be more data-driven, trust in the data used to make decisions becomes more critical. Without data quality processes and tools, enterprises may make decisions based on old, incomplete, incorrect or poorly organized data. The precise measure of quality will depend on the individual use case, but important characteristics include accuracy, completeness, consistency, timeliness and validity.

Creating a “single version of the truth” that provides an agreed definition of customers, products, suppliers or workers is a perpetual challenge for many enterprises. MDM is the practice of establishing and protecting foundational reference data used by an enterprise to provide an agreed list of entities that can be shared throughout the organization. MDM encompasses data validation, matching and merging duplicate records and enriching data with related information, as well as data modeling, which documents the relationships between data elements.

Data intelligence provides a holistic view of data production and consumption, enabling data administrators to understand and manage the use of data in business intelligence (BI) and AI initiatives and accelerate strategic data-democratization initiatives to provide data analysts and business users with governed self-service access to data across an enterprise. Data intelligence platforms provide a combination of data inventory, data discovery and metadata management functionality, as well as data governance, data quality and data lineage to ensure that business users and data analysts can find and access the data they need. Analytics and data leaders benefit from key metrics on data production and consumption, including the value generated by data projects. I assert that through 2027, enterprises will prioritize data intelligence software providers capable of providing a holistic view of data production and data consumption across their organization.

Our Data Management Buyers Guide provides a holistic view of a software provider’s ability to deliver the combination of functionality that provides the complete scope of data management with either a single product or suite of products. As such, the Data Management Buyers Guide includes the full breadth of data management functionality.
Our assessment also considered whether the functionality in question was available in a single offering or as a suite of products or cloud services.

The ISG Buyers Guide™ for Data Management evaluates software providers and products in key areas, including data governance, data intelligence, data quality, master data management and data integration. To be considered for inclusion in the Data Platforms Buyers Guide, a product must be marketed as a data management platform or address at least three of the following functional areas: data governance, data intelligence, data quality, master data management and data integration.

This research evaluates the following software providers that offer products that address key elements of data management as we define it: Actian, Alation, Alibaba Cloud, Ataccama, AWS, Cloud Software Group, Collibra, Databricks, Experian, Google Cloud, Huawei Cloud, IBM, Informatica, Microsoft, Oracle, Pentaho, Precisely, Qlik, Quest, Reltio, Rocket Software, SAP, SAS Institute, Securiti, Snowflake, Syniti and Tencent Cloud.

This research-based index evaluates the full business and information technology value of data management software offerings. We encourage you to learn more about our Buyers Guide and its effectiveness as a provider selection and RFI/RFP tool.

We urge organizations to do a thorough job of evaluating data management offerings in this Buyers Guide as both the results of our in-depth analysis of these software providers and as an evaluation methodology. The Buyers Guide can be used to evaluate existing suppliers, plus provides evaluation criteria for new projects. Using it can shorten the cycle time for an RFP and the definition of an RFI.

The Buyers Guide for Data Management in 2025 finds Informatica first on the list, followed by IBM and Oracle.

Software providers that rated in the top three of any category ﹘ including the product and customer experience dimensions ﹘ earn the designation of Leader.

The Leaders in Product Experience are:

  • Informatica.
  • IBM.
  • Oracle.

The Leaders in Customer Experience are:

  • Databricks.
  • Oracle.
  • Informatica.

The Leaders across any of the seven categories are:

  • Oracle, which has achieved this rating in six of the seven categories.
  • Databricks and Informatica in five categories.
  • Google Cloud in two categories.
  • Actian, IBM and Pentaho in one category.

 

The overall performance chart provides a visual representation of how providers rate across product and customer experience. Software providers with products scoring higher in a weighted rating of the five product experience categories place farther to the right. The combination of ratings for the two customer experience categories determines their placement on the vertical axis. As a result, providers that place closer to the upper-right are “exemplary” and rated higher than those closer to the lower-left and identified as providers of “merit.” Software providers that excelled at customer experience over product experience have an “assurance” rating, and those excelling instead in product experience have an “innovative” rating.

Note that close provider scores should not be taken to imply that the packages evaluated are functionally identical or equally well-suited for use by every enterprise or process. Although there is a high degree of commonality in how organizations handle data management, there are many idiosyncrasies and differences that can make one provider’s offering a better fit than another.

ISG Research has made every effort to encompass in this Buyers Guide the overall product and customer experience from our data management blueprint, which we believe reflects what a well-crafted RFP should contain. Even so, there may be additional areas that affect which software provider and products best fit an enterprise’s particular requirements. Therefore, while this research is complete as it stands, utilizing it in your own organizational context is critical to ensure that products deliver the highest level of support for your projects.

You can find more details on our community as well as on our expertise in the research for this Buyers Guide.