Matt leads the software research and advisory for the Analytics and Data expertise at ISG Software Research, covering software that improves the utilization of information across business and IT. His focus areas of coverage include analytics, data intelligence, data operations, data platforms, and streaming and events. Matt’s specialization is in the operational and analytical use of data and use of AI where enterprises can modernize their approaches to accelerate the value realization of technology investments in support of hybrid and multi-cloud architecture. Matt has been an industry analyst for more than a decade and has pioneered the coverage of emerging data platforms including NoSQL and NewSQL databases, data lakes, and cloud-based data processing. He is a graduate of Bournemouth University.
narration area
Executive Summary
Data Products
The rise of natural language analytics and generative artificial intelligence has accelerated enterprise initiatives aimed at data democratization—making data accessible to business decision makers without requiring them to master complex business intelligence tools. These advances have also underscored the need for shared semantic models, standardized business metrics and technologies that support the creation, sharing and consumption of reusable data products. As enterprises embrace data democratization, they increasingly recognize that information must be packaged, maintained and governed with the same discipline applied to any other enterprise asset.
ISG Research defines data products as the outcome of data initiatives developed with product thinking and delivered as reusable assets that can be discovered and consumed on a self-service basis. Each data product includes its associated data contracts and feedback mechanisms to ensure continuous quality improvement and transparency. Many enterprises first encountered this concept through data mesh, an organizational and cultural framework built on four principles: domain-oriented ownership, self-serve data infrastructure, federated governance and data as a product. While these principles reinforce one another, data as a product has emerged as a stand-alone discipline, emphasizing the need to design, deliver and maintain data outputs that can be shared and reused across the business.
The concept evolved in response to long-standing limitations in how enterprises traditionally delivered analytics. Historically, data assets such as reports, data marts or algorithms were built in isolated projects led by centralized IT teams. Each project created a silo of data optimized for a single purpose, often with duplication and limited reuse. Applying product thinking changes this model. It ensures that data is treated as a continuously maintained product designed for discoverability, usability and reusability. A data product can be a domain-specific data set, an algorithm, a machine learning model or even an operational application. The format is less important than the principle that guides its creation: the outcome must serve multiple use cases and be designed for ongoing improvement through feedback.
Product thinking also reinforces accountability. With domain-oriented ownership, business functions are responsible for managing and sharing the data they generate through standard interfaces and interoperable formats. This alignment between ownership and expertise improves data quality and timeliness. ISG asserts that by 2027, more than 3 in 5 enterprises will adopt technologies to facilitate the delivery of data as a product as they adapt their cultural and organizational approaches to domain-based data ownership. The result is a cultural shift in which data becomes both a shared enterprise asset and a business capability that fuels agility, analytics and innovation.
To achieve this transformation, data owners must behave like product managers. They must understand how data will be used across the enterprise and anticipate consumer needs. Product thinking requires transparency about the purpose, reliability and service expectations of each data product. This transparency is provided through data contracts, formal agreements between data owners and consumers that outline data structure, meaning, service-level expectations and licensing terms. Data contracts establish confidence that data products are accurate, consistent and up to date, enabling decision makers to rely on them for critical business insights. Complementing these contracts are data observability metrics, which monitor attributes such as validity, timeliness and completeness. Together, contracts and observability foster trust in data and provide clear expectations between data producers and consumers.
As demand for governed, reusable data increases, enterprises are turning to dedicated data product platforms designed to support the full lifecycle of development, publication and consumption. These platforms provide integrated environments for creating and versioning data products, tracking lineage, managing change and maintaining consistent metadata. Built-in templates help standardize data contracts and classification schemes. Self-service portals allow users to browse, discover and request access to data products while offering feedback, ratings and recommendations. Administrators and data owners can monitor usage patterns, manage dependencies and resolve issues, ensuring visibility into how data products are being applied across the business.
A robust data product platform must go beyond publishing and discovery to include native or integrated data operations capabilities. These include pipeline development and orchestration, testing environments and observability tools that track quality and lineage from source to consumer. Advanced solutions embed artificial intelligence to automate classification, tag relationships between data products and detect anomalies or duplication across domains. They also apply AI to assist in the development of new data products, recommend relevant assets to users and identify areas where data quality issues affect business outcomes.
As enterprises broaden their approach to data sharing, some platforms extend functionality to external audiences, supporting data monetization and partnerships. These capabilities include portals for licensing and pricing, compliance management for data sharing and APIs for controlled external access. While most data product initiatives today focus on internal sharing, extending to data-as-a-service represents a natural progression for organizations seeking to commercialize their high-value datasets while maintaining strict data governance and usage transparency.
The adoption of data as a product elevates the importance of foundational capabilities such as governance, cataloging and data quality. Making data available on a self-service basis depends on a shared understanding of data definitions, consistent entity resolution and interoperability across tools and domains. Many providers of data catalog software have expanded into this area, integrating features for data product development, discovery and management. These enhancements position catalog vendors as early leaders in enabling data 
product strategies. In parallel, providers of data observability software such as Monte Carlo and Sifflet are adapting their tools to group related data assets into domain-specific use cases. While they offer visibility into performance and quality, they generally do not support the full cycle of data product discovery, access and consumption required for inclusion in the ISG Data Products Buyers Guide.
Enterprises adopting data as a product can expect to accelerate the delivery of analytics and AI initiatives, reduce duplication of effort and enhance trust in the data used for strategic decision-making.
Enterprises adopting data as a product can expect to accelerate the delivery of analytics and AI initiatives, reduce duplication of effort and enhance trust in the data used for strategic decision-making. To succeed, they should evaluate both cultural readiness and technology maturity. ISG recommends that enterprises begin by identifying domains best suited to own and maintain data products, then implement platforms that align to governance and self-service priorities. Buyers should assess the scalability, automation and interoperability of available solutions while considering vendor maturity and roadmap transparency.
The 2025 ISG Buyers Guide™ for Data Products evaluates software providers and products in key areas, including the development, classification, consumption, discovery and management of data products. This research evaluates the following software providers: Actian, Alation, Alteryx, Astronomer, Ataccama, Atlan, Collibra, Confluent, Databricks, DataGalaxy, DataOps.live, Denodo, Domo, Dremio, Google Cloud, Harbr Data, IBM, Informatica, K2view, Microsoft, One Data, Palantir, Qlik, SAP, Snowflake and Starburst.
Buyers Guide Overview
ISG Research has conducted market research for over two decades across vertical industries, business applications, AI and IT. We have designed the ISG Buyers Guide™ to provide a balanced perspective of software providers and products that is rooted in an understanding of business and IT requirements. Utilization of our research methodology and decades of experience enables our Buyers Guide to be an effective method to assess and select software providers and products. The findings of this research provide a comprehensive approach to rating software providers and rank their ability to meet specific product and customer experience requirements.
ISG Research has designed the Buyers Guide to provide a balanced perspective of software providers and products that is rooted in an understanding of business and IT requirements.
The 2025 ISG Buyers Guide™ for Data Products is the distillation of continuous market and product research. It is an assessment of how well software providers’ offerings address enterprises’ requirements for data products software. The Value Index methodology is structured to support a request for information (RFI) for a request for proposal (RFP) process by incorporating all criteria needed to evaluate, select, utilize and maintain relationships with software providers. The ISG Buyers Guide evaluates customer experience and the product experience in its capability and platform.
The structure of the research reflects our understanding that the effective evaluation of software providers and products involves far more than just examining product features, potential revenue or customers generated from a provider’s marketing and sales efforts. It can ensure the best long-term relationship and value achieved from a resource and financial investment We believe it is important to take a comprehensive, research-based approach, since making the wrong choice of data products software can raise the total cost of ownership, lower the return on investment and hamper an enterprise’s ability to reach its potential. In addition, this approach can reduce the project’s development and deployment time and eliminate the risk of relying on opinions or historical biases.
ISG Research believes that an objective review of existing and potential new software providers and products is a critical strategy for the adoption and implementation of data products software. An enterprise’s review should include a thorough analysis of both what is possible and what is relevant. We urge enterprises to do a thorough job of evaluating data products software and offer this Buyers Guide as both the results of our in-depth analysis of these providers and as an evaluation methodology.
Key Takeaways
Data products represent a new model for data management that combines governance, automation and self-service delivery. As enterprises advance toward data democratization, they are formalizing how data is packaged, maintained and reused as a governed business asset. The ISG Buyers Guide™ for Data Products highlights the convergence of data cataloging, observability and orchestration into unified platforms that enable product-based data delivery. These platforms promote transparency, trust and reusability while accelerating analytics and AI initiatives across the enterprise.
Software Provider Summary
The ISG Buyers Guide™ for Data Products evaluates software providers offering products that support data product development, classification, discovery and consumption. The research assessed 22 providers, with Databricks ranking highest overall, followed by Domo and Pentaho. Providers were evaluated on Product Experience and Customer Experience criteria and this report provides the results for each provider along with strengths and areas for improvement.
Product Experience Insights
Product Experience evaluates how effectively providers support the creation, management and deployment of governed, reusable data assets. Leaders in this category, Databricks, Domo and Pentaho, demonstrated balanced strength in both Capability and Platform performance. The Capability assessment reviewed 95 function points across nine sections, while the Platform evaluation examined adaptability, manageability, reliability and usability. Leaders demonstrated strong integration across data domains and scalable architectures that promote automation and collaboration.
Customer Experience Value
Customer Experience measures provider commitment, engagement quality and lifecycle support. Databricks, Informatica and Alteryx achieved the highest ratings for transparency, customer focus and service quality. Providers that did not perform as well often lacked clear articulation of customer outcomes or accessible evidence of value realization. These shortcomings reflected insufficient documentation of customer success programs and inconsistent communication around product performance.
Strategic Recommendations
Enterprises implementing data as a product should select platforms that integrate cataloging, observability and automation to manage the full lifecycle of data assets. Solutions that support domain-based ownership and enforce data contracts will strengthen trust and accountability. Decision-makers should evaluate providers based on governance, interoperability and self-service enablement. Investing in mature data product platforms will accelerate analytics delivery and enhance the organization’s ability to operationalize data as a strategic business asset.
How To Use This Buyers Guide
Evaluating Software Providers: The Process
We recommend using the Buyers Guide to assess and evaluate new or existing software providers for your enterprise. The market research can be used as an evaluation framework to assess existing approaches and software providers or establish a formal request for information from providers on products and customer experience and will shorten the cycle time when creating an RFI. The steps listed below provide a process that can facilitate best possible outcomes in the most efficient manner.
- Define the business case and goals.
Define the mission and business case for investment and the expected outcomes from your organizational and technological efforts.
- Specify the business and IT needs.
Defining the business and IT requirements helps identify what specific capabilities are required with respect to people, processes, information and technology.
- Assess the required roles and responsibilities.
Identify the individuals required for success at every level of the enterprise from executives to frontline workers and determine the needs of each.
- Outline the project’s critical path.
What needs to be done, in what order and who will do it? This outline should make clear the prior dependencies at each step of the project plan.
- Ascertain the technology approach.
Determine the business and technology approach that most closely aligns to your enterprise’s requirements.
- Establish software provider evaluation criteria.
Utilize the product experience: capability and platform with support for adaptability, manageability, reliability and usability, and the customer experience in TCO/ROI and Validation.
- Evaluate and select the software provider and products properly.
Apply a weighting the evaluation categories in the evaluation criteria to reflect your enterprise’s priorities to determine the short list of software providers and products.
- Establish the business initiative team to start the project.
Identify who will lead the project and the members of the team needed to plan and execute it with timelines, priorities and resources.
Using the ISG Buyers Guide and process provides enterprises a clear, structured approach to making smarter software and business investment decisions. It ensures alignment between strategy, people, processes and technology while reducing risk, saving time and improving outcomes. The ISG approach promotes data-driven decision-making and collaboration, helping choose the right software providers for maximum value and return on investment.
The Findings
The software providers and products evaluated in the research provide product and customer experiences, but not everything offered is equally valuable to every enterprise or is needed to operate in business processes and use cases. Moreover, the existence of too many capabilities in products may be a negative factor for an enterprise if it introduces unnecessary complexity. Nonetheless, you may decide that a more comprehensive set of capabilities in the product is important, and where they match your enterprise’s requirements.
An effective customer relationship with a software provider is vital to the success of any investment. The overall customer experience and the full lifecycle of engagement play a key role in ensuring satisfaction and long-term success. Providers with dedicated customer leadership, such as chief customer officers, tend to invest more deeply in these relationships and prioritize customer outcomes to TCO and ROI expectations. It is equally important that this commitment to customer success is clearly demonstrated throughout the provider’s website, buying process and customer journey.
Overall Scoring of Software Providers Across Categories
The research finds Databricks atop the list, followed by Domo and Pentaho. Providers that place in the top three of a category earn the designation of Leader. Databricks has done so in five categories; Domo and Pentaho in three; Informatica in two and Alteryx and Microsoft in one category.
The overall representation of the research below places the rating of the Product Experience and Customer Experience on the x and y axes, respectively, to provide a visual representation and classification of the software providers. Those providers whose Product Experience have above median weighted performance to the axis in aggregate of the two product categories place farther to the right, while the performance and weighting for the Customer Experience category determines placement on the vertical axis. In short, software providers that place closer to the upper-right on this chart performed better than those closer to the lower-left.
The research categorizes and rates software providers into one of four categories: Assurance, Exemplary, Merit or Innovative. This representation of software providers’ weighted performance in meeting the requirements in product and customer experience.
Exemplary: This rating (upper right) represents those that performed above median in Product and Customer Experience requirements. The providers rated Exemplary are: Actian, Alation, Alteryx, AWS, Databricks, Denodo, Domo, IBM, Informatica, Microsoft, Pentaho and SAP.
Innovative: This rating (lower right) represents those that performed above median in Product Experience but not in Customer Experience. The provider rated Innovative is: DataOps.live.
Assurance: This rating (upper left) represents those that performed above median in Customer Experience but not in Product Experience. The provider rated Assurance is: Collibra.
Merit: This rating (lower left) represents those that did not surpass the median in Customer or Product Experience. The providers rated Merit are: Atlan, Confluent, DataGalaxy, Dremio, Harbr, K2view, One Data, Palantir, Qlik, RightData, Snowflake and Starburst.
We advise enterprises to use this research as a supplement to their own evaluations, recognizing that ratings or rankings do not solely represent the value of a provider nor indicate universal suitability of a set of products.
Product Experience
The process of researching products to address an enterprise’s needs should be comprehensive and evaluate specific capabilities and the underlying platform to the product experience. Our evaluation of the Product Experience examines the lifecycle of onboarding, configuration, operations, usage and maintenance. Too often, software providers are not evaluated for the entirety of the product; instead, they are evaluated on market execution and vision of the future.
The research results in Product Experience are ranked at 80%, or four-fifths, using the underlying weighted performance. Importance was placed on the categories as follows: Capability (40%) and Platform (40%). Databricks, Domo and Pentaho were designated Product Experience Leaders.
Customer Experience
The importance of a customer relationship with a software provider is essential to the actual success of the products and technology. The evaluation of the Customer Experience and the entire lifecycle an enterprise has with its software provider is critical for ensuring satisfaction in working with that provider. The ISG Buyers Guide examines a software provider’s customer commitment, viability, customer success, sales and onboarding, product roadmap and services with partners and support. The customer experience category also investigates the TCO/ROI and how well a software provider demonstrates the product’s overall value, cost and benefits, including the tools and resources to evaluate these factors.
The research results in Customer Experience are ranked at 20%, or one-fifth of the 100% index, and represent the underlying provider validation and TCO/ROI requirements as they relate to the framework of commitment and value to the software provider-customer relationship.
The software providers that evaluated the highest in the Customer Experience category are Databricks, Informatica and Alteryx. These category leaders best communicate commitment and dedication to customer needs.
Software providers that did not perform well in this category were unable to provide or make sufficient information readily available to demonstrate success or articulate their commitment to customer experience. The use of a software provider requires continuous investment, so a holistic evaluation must include examination of how they support their customer experience.
Appendix: Software Provider Inclusion
For inclusion in the 2025 ISG Buyers Guide™ for Data Products, a software provider must be in good standing financially and ethically, have at least $10 million in annual or projected revenue verified using independent sources, sell products and provide support on at least two continents, and have at least 50 employees. The principal source of the relevant business unit’s revenue must be software-related, and there must have been at least one major software release in the last 12 months.
Data as a product is the process of applying product thinking to data initiatives to ensure that the outcome—the data product—is designed to be shared and reused for multiple use-cases across the business. Data product platforms provide an environment for the development, publication and consumption of data products.
To be included in the Data Products Buyers Guide, the product(s) must be marketed as a data products platform or address the following functional areas, which are mapped into Buyers Guide capability criteria:
- DataOps
- Collaboration
- Acceleration
- Automation
- Ecosystem integration
- Data product development
- Data product classification
- Data product consumption
- Data product management
The research is designed to be independent of the specifics of software provider packaging and pricing. To represent the real-world environment in which businesses operate, we include providers that offer suites or packages of products that may include relevant individual modules or applications. If a software provider is actively marketing, selling and developing a product for the general market and it is reflected on the provider’s website that the product is within the scope of the research, that provider is automatically evaluated for inclusion.
All software providers that offer relevant data products platforms and meet the inclusion requirements were invited to participate in the evaluation process at no cost to them.
Software providers that meet our inclusion criteria but did not completely participate in our Buyers Guide were assessed solely on publicly available information. As this could have a significant impact on classification and ratings, we recommend additional scrutiny when evaluating those providers.
Products Evaluated
| Provider | Product Names | Version | Release Month/Year |
|---|---|---|---|
| Actian | Actian Data Intelligence Platform | v. Spring 2025 | June 2025 |
| Alation | Alation Agentic Data Intelligence Platform | v. 2025.3 | September 2025 |
| Alteryx | Alteryx Connect | v. 2025.1 | May 2025 |
| Atlan | Atlan | NA | September 2025 |
| AWS | Amazon SageMaker | NA | August 2025 |
| Collibra | Collibra Platform | v. 2025.09 | September 2025 |
| Confluent | Confluent Cloud | NA | September 2025 |
| Databricks | Databricks Data Intelligence Platform | NA | September 2025 |
| DataGalaxy | DataGalaxy | NA | September 2025 |
| DataOps.live | DataOps.live | NA | September 2025 |
| Denodo | Denodo Platform | v. 9.2 | April 2025 |
| Domo | Domo | v. 2025 Release 4 | July 2025 |
| Dremio | Dremio Intelligent Lakehouse Platform | v. 25.2.18 | August 2025 |
| Harbr | Harbr | v. 5.2.1 | September 2025 |
| IBM | IBM watsonx.data Intelligence | NA | September 2025 |
| Informatica | Informatica Intelligent Data Management Cloud | NA | August 2025 |
| K2view | K2view Data Product Platform | v. 8.3.0 | August 2025 |
| Microsoft | Microsoft Purview | NA | September 2025 |
| One Data | One Data | NA | September 2025 |
| Palantir | Palantir Foundry | NA | September 2025 |
| Pentaho | Pentaho Data Catalog | v. 10.2.8 | September 2025 |
| Qlik | Qlik Talend Cloud | NA | September 2025 |
| RightData | DataMarket | v. 2.1.0 | December 2024 |
| SAP | SAP Business Data Cloud | NA | September 2025 |
| Snowflake | Snowflake Platform | NA | September 2025 |
| Starburst | Starburst Galaxy | NA | September 2025 |
Providers of Promise
We did not include software providers that, as a result of our research and analysis, did not satisfy the criteria for inclusion in this Buyers Guide. These are listed below as “Providers of Promise.”
| Provider | Product | Annual Revenue >$10M | Operates on 2 Continents | At Least 50 Employees | Product GA |
|---|---|---|---|---|---|
| Acryl Data | DataHub | No | Yes | Yes | Yes |
| Ascend | Ascend | No | Yes | Yes | Yes |
| Immuta | Data Marketplace | No | Yes | Yes | Yes |
| Keboola | Keboola | No | Yes | Yes | Yes |
| Modern | DataOS | No | Yes | No | Yes |
| Nexla | Nexla | No | Yes | No | Yes |
| Nextdata | Nextdata OS | Yes | Yes | Yes | No |
| Palantir | Foundry | No | Yes | Yes | Yes |
| Promethium | Promethium | No | Yes | No | Yes |
Executive Summary
Data Products
The rise of natural language analytics and generative artificial intelligence has accelerated enterprise initiatives aimed at data democratization—making data accessible to business decision makers without requiring them to master complex business intelligence tools. These advances have also underscored the need for shared semantic models, standardized business metrics and technologies that support the creation, sharing and consumption of reusable data products. As enterprises embrace data democratization, they increasingly recognize that information must be packaged, maintained and governed with the same discipline applied to any other enterprise asset.
ISG Research defines data products as the outcome of data initiatives developed with product thinking and delivered as reusable assets that can be discovered and consumed on a self-service basis. Each data product includes its associated data contracts and feedback mechanisms to ensure continuous quality improvement and transparency. Many enterprises first encountered this concept through data mesh, an organizational and cultural framework built on four principles: domain-oriented ownership, self-serve data infrastructure, federated governance and data as a product. While these principles reinforce one another, data as a product has emerged as a stand-alone discipline, emphasizing the need to design, deliver and maintain data outputs that can be shared and reused across the business.
The concept evolved in response to long-standing limitations in how enterprises traditionally delivered analytics. Historically, data assets such as reports, data marts or algorithms were built in isolated projects led by centralized IT teams. Each project created a silo of data optimized for a single purpose, often with duplication and limited reuse. Applying product thinking changes this model. It ensures that data is treated as a continuously maintained product designed for discoverability, usability and reusability. A data product can be a domain-specific data set, an algorithm, a machine learning model or even an operational application. The format is less important than the principle that guides its creation: the outcome must serve multiple use cases and be designed for ongoing improvement through feedback.
Product thinking also reinforces accountability. With domain-oriented ownership, business functions are responsible for managing and sharing the data they generate through standard interfaces and interoperable formats. This alignment between ownership and expertise improves data quality and timeliness. ISG asserts that by 2027, more than 3 in 5 enterprises will adopt technologies to facilitate the delivery of data as a product as they adapt their cultural and organizational approaches to domain-based data ownership. The result is a cultural shift in which data becomes both a shared enterprise asset and a business capability that fuels agility, analytics and innovation.
To achieve this transformation, data owners must behave like product managers. They must understand how data will be used across the enterprise and anticipate consumer needs. Product thinking requires transparency about the purpose, reliability and service expectations of each data product. This transparency is provided through data contracts, formal agreements between data owners and consumers that outline data structure, meaning, service-level expectations and licensing terms. Data contracts establish confidence that data products are accurate, consistent and up to date, enabling decision makers to rely on them for critical business insights. Complementing these contracts are data observability metrics, which monitor attributes such as validity, timeliness and completeness. Together, contracts and observability foster trust in data and provide clear expectations between data producers and consumers.
As demand for governed, reusable data increases, enterprises are turning to dedicated data product platforms designed to support the full lifecycle of development, publication and consumption. These platforms provide integrated environments for creating and versioning data products, tracking lineage, managing change and maintaining consistent metadata. Built-in templates help standardize data contracts and classification schemes. Self-service portals allow users to browse, discover and request access to data products while offering feedback, ratings and recommendations. Administrators and data owners can monitor usage patterns, manage dependencies and resolve issues, ensuring visibility into how data products are being applied across the business.
A robust data product platform must go beyond publishing and discovery to include native or integrated data operations capabilities. These include pipeline development and orchestration, testing environments and observability tools that track quality and lineage from source to consumer. Advanced solutions embed artificial intelligence to automate classification, tag relationships between data products and detect anomalies or duplication across domains. They also apply AI to assist in the development of new data products, recommend relevant assets to users and identify areas where data quality issues affect business outcomes.
As enterprises broaden their approach to data sharing, some platforms extend functionality to external audiences, supporting data monetization and partnerships. These capabilities include portals for licensing and pricing, compliance management for data sharing and APIs for controlled external access. While most data product initiatives today focus on internal sharing, extending to data-as-a-service represents a natural progression for organizations seeking to commercialize their high-value datasets while maintaining strict data governance and usage transparency.
The adoption of data as a product elevates the importance of foundational capabilities such as governance, cataloging and data quality. Making data available on a self-service basis depends on a shared understanding of data definitions, consistent entity resolution and interoperability across tools and domains. Many providers of data catalog software have expanded into this area, integrating features for data product development, discovery and management. These enhancements position catalog vendors as early leaders in enabling data product strategies. In parallel, providers of data observability software such as Monte Carlo and Sifflet are adapting their tools to group related data assets into domain-specific use cases. While they offer visibility into performance and quality, they generally do not support the full cycle of data product discovery, access and consumption required for inclusion in the ISG Data Products Buyers Guide.
Enterprises adopting data as a product can expect to accelerate the delivery of analytics and AI initiatives, reduce duplication of effort and enhance trust in the data used for strategic decision-making.
Enterprises adopting data as a product can expect to accelerate the delivery of analytics and AI initiatives, reduce duplication of effort and enhance trust in the data used for strategic decision-making. To succeed, they should evaluate both cultural readiness and technology maturity. ISG recommends that enterprises begin by identifying domains best suited to own and maintain data products, then implement platforms that align to governance and self-service priorities. Buyers should assess the scalability, automation and interoperability of available solutions while considering vendor maturity and roadmap transparency.
The 2025 ISG Buyers Guide™ for Data Products evaluates software providers and products in key areas, including the development, classification, consumption, discovery and management of data products. This research evaluates the following software providers: Actian, Alation, Alteryx, Astronomer, Ataccama, Atlan, Collibra, Confluent, Databricks, DataGalaxy, DataOps.live, Denodo, Domo, Dremio, Google Cloud, Harbr Data, IBM, Informatica, K2view, Microsoft, One Data, Palantir, Qlik, SAP, Snowflake and Starburst.
Buyers Guide Overview
ISG Research has conducted market research for over two decades across vertical industries, business applications, AI and IT. We have designed the ISG Buyers Guide™ to provide a balanced perspective of software providers and products that is rooted in an understanding of business and IT requirements. Utilization of our research methodology and decades of experience enables our Buyers Guide to be an effective method to assess and select software providers and products. The findings of this research provide a comprehensive approach to rating software providers and rank their ability to meet specific product and customer experience requirements.
ISG Research has designed the Buyers Guide to provide a balanced perspective of software providers and products that is rooted in an understanding of business and IT requirements.
The 2025 ISG Buyers Guide™ for Data Products is the distillation of continuous market and product research. It is an assessment of how well software providers’ offerings address enterprises’ requirements for data products software. The Value Index methodology is structured to support a request for information (RFI) for a request for proposal (RFP) process by incorporating all criteria needed to evaluate, select, utilize and maintain relationships with software providers. The ISG Buyers Guide evaluates customer experience and the product experience in its capability and platform.
The structure of the research reflects our understanding that the effective evaluation of software providers and products involves far more than just examining product features, potential revenue or customers generated from a provider’s marketing and sales efforts. It can ensure the best long-term relationship and value achieved from a resource and financial investment We believe it is important to take a comprehensive, research-based approach, since making the wrong choice of data products software can raise the total cost of ownership, lower the return on investment and hamper an enterprise’s ability to reach its potential. In addition, this approach can reduce the project’s development and deployment time and eliminate the risk of relying on opinions or historical biases.
ISG Research believes that an objective review of existing and potential new software providers and products is a critical strategy for the adoption and implementation of data products software. An enterprise’s review should include a thorough analysis of both what is possible and what is relevant. We urge enterprises to do a thorough job of evaluating data products software and offer this Buyers Guide as both the results of our in-depth analysis of these providers and as an evaluation methodology.
Key Takeaways
Data products represent a new model for data management that combines governance, automation and self-service delivery. As enterprises advance toward data democratization, they are formalizing how data is packaged, maintained and reused as a governed business asset. The ISG Buyers Guide™ for Data Products highlights the convergence of data cataloging, observability and orchestration into unified platforms that enable product-based data delivery. These platforms promote transparency, trust and reusability while accelerating analytics and AI initiatives across the enterprise.
Software Provider Summary
The ISG Buyers Guide™ for Data Products evaluates software providers offering products that support data product development, classification, discovery and consumption. The research assessed 22 providers, with Databricks ranking highest overall, followed by Domo and Pentaho. Providers were evaluated on Product Experience and Customer Experience criteria and this report provides the results for each provider along with strengths and areas for improvement.
Product Experience Insights
Product Experience evaluates how effectively providers support the creation, management and deployment of governed, reusable data assets. Leaders in this category, Databricks, Domo and Pentaho, demonstrated balanced strength in both Capability and Platform performance. The Capability assessment reviewed 95 function points across nine sections, while the Platform evaluation examined adaptability, manageability, reliability and usability. Leaders demonstrated strong integration across data domains and scalable architectures that promote automation and collaboration.
Customer Experience Value
Customer Experience measures provider commitment, engagement quality and lifecycle support. Databricks, Informatica and Alteryx achieved the highest ratings for transparency, customer focus and service quality. Providers that did not perform as well often lacked clear articulation of customer outcomes or accessible evidence of value realization. These shortcomings reflected insufficient documentation of customer success programs and inconsistent communication around product performance.
Strategic Recommendations
Enterprises implementing data as a product should select platforms that integrate cataloging, observability and automation to manage the full lifecycle of data assets. Solutions that support domain-based ownership and enforce data contracts will strengthen trust and accountability. Decision-makers should evaluate providers based on governance, interoperability and self-service enablement. Investing in mature data product platforms will accelerate analytics delivery and enhance the organization’s ability to operationalize data as a strategic business asset.
How To Use This Buyers Guide
Evaluating Software Providers: The Process
We recommend using the Buyers Guide to assess and evaluate new or existing software providers for your enterprise. The market research can be used as an evaluation framework to assess existing approaches and software providers or establish a formal request for information from providers on products and customer experience and will shorten the cycle time when creating an RFI. The steps listed below provide a process that can facilitate best possible outcomes in the most efficient manner.
- Define the business case and goals.
Define the mission and business case for investment and the expected outcomes from your organizational and technological efforts.
- Specify the business and IT needs.
Defining the business and IT requirements helps identify what specific capabilities are required with respect to people, processes, information and technology.
- Assess the required roles and responsibilities.
Identify the individuals required for success at every level of the enterprise from executives to frontline workers and determine the needs of each.
- Outline the project’s critical path.
What needs to be done, in what order and who will do it? This outline should make clear the prior dependencies at each step of the project plan.
- Ascertain the technology approach.
Determine the business and technology approach that most closely aligns to your enterprise’s requirements.
- Establish software provider evaluation criteria.
Utilize the product experience: capability and platform with support for adaptability, manageability, reliability and usability, and the customer experience in TCO/ROI and Validation.
- Evaluate and select the software provider and products properly.
Apply a weighting the evaluation categories in the evaluation criteria to reflect your enterprise’s priorities to determine the short list of software providers and products.
- Establish the business initiative team to start the project.
Identify who will lead the project and the members of the team needed to plan and execute it with timelines, priorities and resources.
Using the ISG Buyers Guide and process provides enterprises a clear, structured approach to making smarter software and business investment decisions. It ensures alignment between strategy, people, processes and technology while reducing risk, saving time and improving outcomes. The ISG approach promotes data-driven decision-making and collaboration, helping choose the right software providers for maximum value and return on investment.
The Findings
The software providers and products evaluated in the research provide product and customer experiences, but not everything offered is equally valuable to every enterprise or is needed to operate in business processes and use cases. Moreover, the existence of too many capabilities in products may be a negative factor for an enterprise if it introduces unnecessary complexity. Nonetheless, you may decide that a more comprehensive set of capabilities in the product is important, and where they match your enterprise’s requirements.
An effective customer relationship with a software provider is vital to the success of any investment. The overall customer experience and the full lifecycle of engagement play a key role in ensuring satisfaction and long-term success. Providers with dedicated customer leadership, such as chief customer officers, tend to invest more deeply in these relationships and prioritize customer outcomes to TCO and ROI expectations. It is equally important that this commitment to customer success is clearly demonstrated throughout the provider’s website, buying process and customer journey.
Overall Scoring of Software Providers Across Categories
The research finds Databricks atop the list, followed by Domo and Pentaho. Providers that place in the top three of a category earn the designation of Leader. Databricks has done so in five categories; Domo and Pentaho in three; Informatica in two and Alteryx and Microsoft in one category.
The overall representation of the research below places the rating of the Product Experience and Customer Experience on the x and y axes, respectively, to provide a visual representation and classification of the software providers. Those providers whose Product Experience have above median weighted performance to the axis in aggregate of the two product categories place farther to the right, while the performance and weighting for the Customer Experience category determines placement on the vertical axis. In short, software providers that place closer to the upper-right on this chart performed better than those closer to the lower-left.
The research categorizes and rates software providers into one of four categories: Assurance, Exemplary, Merit or Innovative. This representation of software providers’ weighted performance in meeting the requirements in product and customer experience.
Exemplary: This rating (upper right) represents those that performed above median in Product and Customer Experience requirements. The providers rated Exemplary are: Actian, Alation, Alteryx, AWS, Databricks, Denodo, Domo, IBM, Informatica, Microsoft, Pentaho and SAP.
Innovative: This rating (lower right) represents those that performed above median in Product Experience but not in Customer Experience. The provider rated Innovative is: DataOps.live.
Assurance: This rating (upper left) represents those that performed above median in Customer Experience but not in Product Experience. The provider rated Assurance is: Collibra.
Merit: This rating (lower left) represents those that did not surpass the median in Customer or Product Experience. The providers rated Merit are: Atlan, Confluent, DataGalaxy, Dremio, Harbr, K2view, One Data, Palantir, Qlik, RightData, Snowflake and Starburst.
We advise enterprises to use this research as a supplement to their own evaluations, recognizing that ratings or rankings do not solely represent the value of a provider nor indicate universal suitability of a set of products.
Product Experience
The process of researching products to address an enterprise’s needs should be comprehensive and evaluate specific capabilities and the underlying platform to the product experience. Our evaluation of the Product Experience examines the lifecycle of onboarding, configuration, operations, usage and maintenance. Too often, software providers are not evaluated for the entirety of the product; instead, they are evaluated on market execution and vision of the future.
The research results in Product Experience are ranked at 80%, or four-fifths, using the underlying weighted performance. Importance was placed on the categories as follows: Capability (40%) and Platform (40%). Databricks, Domo and Pentaho were designated Product Experience Leaders.
Customer Experience
The importance of a customer relationship with a software provider is essential to the actual success of the products and technology. The evaluation of the Customer Experience and the entire lifecycle an enterprise has with its software provider is critical for ensuring satisfaction in working with that provider. The ISG Buyers Guide examines a software provider’s customer commitment, viability, customer success, sales and onboarding, product roadmap and services with partners and support. The customer experience category also investigates the TCO/ROI and how well a software provider demonstrates the product’s overall value, cost and benefits, including the tools and resources to evaluate these factors.
The research results in Customer Experience are ranked at 20%, or one-fifth of the 100% index, and represent the underlying provider validation and TCO/ROI requirements as they relate to the framework of commitment and value to the software provider-customer relationship.
The software providers that evaluated the highest in the Customer Experience category are Databricks, Informatica and Alteryx. These category leaders best communicate commitment and dedication to customer needs.
Software providers that did not perform well in this category were unable to provide or make sufficient information readily available to demonstrate success or articulate their commitment to customer experience. The use of a software provider requires continuous investment, so a holistic evaluation must include examination of how they support their customer experience.
Appendix: Software Provider Inclusion
For inclusion in the 2025 ISG Buyers Guide™ for Data Products, a software provider must be in good standing financially and ethically, have at least $10 million in annual or projected revenue verified using independent sources, sell products and provide support on at least two continents, and have at least 50 employees. The principal source of the relevant business unit’s revenue must be software-related, and there must have been at least one major software release in the last 12 months.
Data as a product is the process of applying product thinking to data initiatives to ensure that the outcome—the data product—is designed to be shared and reused for multiple use-cases across the business. Data product platforms provide an environment for the development, publication and consumption of data products.
To be included in the Data Products Buyers Guide, the product(s) must be marketed as a data products platform or address the following functional areas, which are mapped into Buyers Guide capability criteria:
- DataOps
- Collaboration
- Acceleration
- Automation
- Ecosystem integration
- Data product development
- Data product classification
- Data product consumption
- Data product management
The research is designed to be independent of the specifics of software provider packaging and pricing. To represent the real-world environment in which businesses operate, we include providers that offer suites or packages of products that may include relevant individual modules or applications. If a software provider is actively marketing, selling and developing a product for the general market and it is reflected on the provider’s website that the product is within the scope of the research, that provider is automatically evaluated for inclusion.
All software providers that offer relevant data products platforms and meet the inclusion requirements were invited to participate in the evaluation process at no cost to them.
Software providers that meet our inclusion criteria but did not completely participate in our Buyers Guide were assessed solely on publicly available information. As this could have a significant impact on classification and ratings, we recommend additional scrutiny when evaluating those providers.
Products Evaluated
| Provider | Product Names | Version | Release Month/Year |
|---|---|---|---|
| Actian | Actian Data Intelligence Platform | v. Spring 2025 | June 2025 |
| Alation | Alation Agentic Data Intelligence Platform | v. 2025.3 | September 2025 |
| Alteryx | Alteryx Connect | v. 2025.1 | May 2025 |
| Atlan | Atlan | NA | September 2025 |
| AWS | Amazon SageMaker | NA | August 2025 |
| Collibra | Collibra Platform | v. 2025.09 | September 2025 |
| Confluent | Confluent Cloud | NA | September 2025 |
| Databricks | Databricks Data Intelligence Platform | NA | September 2025 |
| DataGalaxy | DataGalaxy | NA | September 2025 |
| DataOps.live | DataOps.live | NA | September 2025 |
| Denodo | Denodo Platform | v. 9.2 | April 2025 |
| Domo | Domo | v. 2025 Release 4 | July 2025 |
| Dremio | Dremio Intelligent Lakehouse Platform | v. 25.2.18 | August 2025 |
| Harbr | Harbr | v. 5.2.1 | September 2025 |
| IBM | IBM watsonx.data Intelligence | NA | September 2025 |
| Informatica | Informatica Intelligent Data Management Cloud | NA | August 2025 |
| K2view | K2view Data Product Platform | v. 8.3.0 | August 2025 |
| Microsoft | Microsoft Purview | NA | September 2025 |
| One Data | One Data | NA | September 2025 |
| Palantir | Palantir Foundry | NA | September 2025 |
| Pentaho | Pentaho Data Catalog | v. 10.2.8 | September 2025 |
| Qlik | Qlik Talend Cloud | NA | September 2025 |
| RightData | DataMarket | v. 2.1.0 | December 2024 |
| SAP | SAP Business Data Cloud | NA | September 2025 |
| Snowflake | Snowflake Platform | NA | September 2025 |
| Starburst | Starburst Galaxy | NA | September 2025 |
Providers of Promise
We did not include software providers that, as a result of our research and analysis, did not satisfy the criteria for inclusion in this Buyers Guide. These are listed below as “Providers of Promise.”
| Provider | Product | Annual Revenue >$10M | Operates on 2 Continents | At Least 50 Employees | Product GA |
|---|---|---|---|---|---|
| Acryl Data | DataHub | No | Yes | Yes | Yes |
| Ascend | Ascend | No | Yes | Yes | Yes |
| Immuta | Data Marketplace | No | Yes | Yes | Yes |
| Keboola | Keboola | No | Yes | Yes | Yes |
| Modern | DataOS | No | Yes | No | Yes |
| Nexla | Nexla | No | Yes | No | Yes |
| Nextdata | Nextdata OS | Yes | Yes | Yes | No |
| Palantir | Foundry | No | Yes | Yes | Yes |
| Promethium | Promethium | No | Yes | No | Yes |
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