Executive Summary

Data Governance

Data governance is integral to an overall data intelligence strategy. Good data governance provides guardrails that enable organizations to act quickly while protecting the business from risks related to regulatory requirements, data-quality issues and data-reliability concerns. It accelerates the delivery of analytics projects, providing the confidence required to make agile business decisions.

Good data governance provides guardrails that enable organizations to act quickly while protecting the business from risks related to regulatory requirements, data-quality issues and data-reliability concerns.

ISG Research defines data governance as enabling enterprises to ensure data is cataloged, trusted and protected, improving business processes to accelerate analytics initiatives while supporting compliance with data privacy, security policies and 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. Improved operational efficiency is another major benefit of data governance, along with reduced cost of existing IT support.

The importance of data governance is well recognized and understood. Almost 9 in 10 participants in our Data Governance Benchmark Research identified data governance as important or very important to the organization. Large enterprises rated data governance as 97% important or very important, and finance, insurance and real estate organizations gave it a 93% important or very important rating. This increase in importance, alongside the growing maturity and expanded functionality available in data governance software, is a contributing factor in its accelerated adoption.

The emergence of the data catalog drove much of the increased focus on data governance. It has become an integral component of enterprise data strategies over the past decade, serving as a conduit for good data governance and facilitating self-service analytics initiatives. The data catalog has become so important that it is easy to forget that, just 10 years ago, it did not exist as a standalone product category. Metadata-based data management functionality have played a role in products for data governance and business intelligence for much longer, but the emergence of the data catalog as a product category provided a platform for metadata-based data inventory and discovery that spans an entire organization, serving multiple departments, use cases and initiatives.

Data catalogs facilitate a holistic view of data production and consumption. They support the requirements of data operators, with capabilities to address internal data governance policies and external regulatory requirements. Data catalogs also support the needs of data consumers with functionality to address self-service data discovery and collaboration. Both are supported by automation, with data catalogs using artificial intelligence and machine learning to accelerate metadata collection, semantic inference, tagging and recommendations.

Initial adoption of data catalog products was led by large organizations embarking on digital transformation and data governance initiatives. Digital native startups, recognizing the importance of data democratization to create a data-driven culture, were also early adopters. Adoption has now spread to organizations of all shapes and sizes. Through 2027, enterprises will increase strategic focus on data catalogs as the intersection of data production and consumption, enabling the self-service creation and sharing of data products based on trusted and governed data sources.

The significance of the data catalog to data governance initiatives is highlighted by our research, indicating that the more data catalog users an enterprise has, the greater trust the organization has in its data and the higher the level of confidence in its ability to govern and manage data across the business. Almost three-quarters (74%) of enterprises with more than 100 data catalog users trust the data used in decision-making and operations, compared to 66% of those with 100 or fewer data catalog users. Similarly, three-quarters (75%) of enterprises with more than 100 data catalog users are confident in the organization’s ability to govern and manage data across the business, compared to 56% of enterprises with 100 or fewer data catalog users.

The role data catalogs play in enabling enterprises to inventory and discover data in data lake environments has contributed to adoption. Further, the evolution of these environments into data lakehouses has increased approaches to store and analyze large volumes of data from multiple applications. Data lakehouse environments based on cloud object storage offer a relatively inexpensive way to store large volumes of data. This includes structured, semi-structured and unstructured data unsuitable for storing and processing in a data warehouse. Additional functionality is required, however, to ensure that all that data is useful from a business context. Due to the complexity of storing and processing large volumes of raw data from multiple operational applications, the data catalog has emerged as a critical resource for providing an inventory of data of varied formats stored in a data lakehouse to be queried by multiple business departments for diverse analytic workloads.

This is not to say that data catalogs are a panacea for data governance. In fact, the proliferation of data catalog functionality in the past decade could contribute to the challenge of effective data usage. Not only are there many standalone data catalog providers, but numerous software providers offer data catalog functionality in data and analytics platforms. Through 2026, more than one-half of all enterprises will continue to utilize multiple data catalog technologies, running the risk of creating silos of information knowledge. Co-opetition among software providers is critical to ensure that multiple data catalogs do not become competing silos of information knowledge. Such an outcome would impede the use of enterprise data for strategic AI initiatives and pose risks in ensuring compliance with regulatory requirements.

In addition to differing regulatory requirements, our research illustrates varying attitudes and approaches to data governance on either side of the Atlantic.

Multinational organizations must be aware of the wide variety of regional data security and privacy requirements. This includes the European Union’s General Data Protection Regulation and similar regulations like the California Consumer Privacy Act. In addition to differing regulatory requirements, our research illustrates varying attitudes and approaches to data governance on either side of the Atlantic: Better regulatory compliance is seen as a benefit of investing in data governance by almost three-quarters of European enterprises, compared to 57% of North American organizations.

Our Data Governance Buyers Guide is designed to provide a holistic view of a software provider’s ability to deliver the combination of functionality that provides a complete view of data governance with either a single product or suite of products. As such, the Data Governance Buyers Guide includes the full breadth of data governance 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 Governance evaluates products based on the governance of real-time data in motion and data at rest, as well as the use of AI to automate and enhance data governance. To be considered for this Buyers Guide, products must include at least one of the following functional areas, which are mapped into the Buyers Guide Capability criteria: data catalog, data lineage and data stewardship.

This research evaluates the following software providers that offer products that address key elements of data governance as we define it: Alation, Alibaba Cloud, Amazon Web Services, Ataccama, Atlan, Collibra, Confluent, Databricks, Google Cloud, Hitachi Vantara, Huawei Cloud, IBM, Informatica, Microsoft, Oracle, Precisely, Qlik, Quest Software, Rocket Software, SAP, SAS Institute, Solace and Syniti.

Buyers Guide Overview

For over two decades, ISG Research has conducted market research in a spectrum of areas across business applications, tools and technologies. We have designed the Buyers Guide to provide a balanced perspective of software providers and products that is rooted in an understanding of the business requirements in any enterprise. 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 undertaking contribute to our comprehensive approach to rating software providers in a manner that is based on the assessments completed by an enterprise.

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 requirements in any enterprise.

The ISG Buyers Guide™ for Data Governance is the distillation of over a year of market and product research efforts. It is an assessment of how well software providers’ offerings address enterprises’ requirements for data governance software. The index is structured to support a request for information (RFI) that could be used in the request for proposal (RFP) process by incorporating all criteria needed to evaluate, select, utilize and maintain relationships with software providers. An effective product and customer experience with a provider can ensure the best long-term relationship and value achieved from a resource and financial investment.

In this Buyers Guide, ISG Research evaluates the software in seven key categories that are weighted to reflect buyers’ needs based on our expertise and research. Five are product-experience related: Adaptability, Capability, Manageability, Reliability, and Usability. In addition, we consider two customer-experience categories: Validation, and Total Cost of Ownership/Return on Investment (TCO/ROI). To assess functionality, one of the components of Capability, we applied the ISG Research Value Index methodology and blueprint, which links the personas and processes for data governance to an enterprise’s requirements.

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. We believe it is important to take a comprehensive, research-based approach, since making the wrong choice of data governance technology can raise the total cost of ownership, lower the return on investment and hamper an enterprise’s ability to reach its full performance potential. In addition, this approach can reduce the project’s development and deployment time and eliminate the risk of relying on a short list of software providers that does not represent a best fit for your enterprise.

ISG Research believes that an objective review of software providers and products is a critical business strategy for the adoption and implementation of data governance software and applications. 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 governance systems and tools and offer this Buyers Guide as both the results of our in-depth analysis of these providers and as an evaluation methodology.

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 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.

1. Define the business case and goals.
   Define the mission and business case for investment and the expected outcomes from your organizational and technology efforts. 
2. Specify the business needs.
Defining the business requirements helps identify what specific capabilities are required with respect to people, processes, information and technology.
3. Assess the required roles and responsibilities.
Identify the individuals required for success at every level of the organization from executives to front line workers and determine the needs of each. 
4. 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. 
5. Ascertain the technology approach.
Determine the business and technology approach that most closely aligns to your organization’s requirements. 
6. Establish technology vendor evaluation criteria.
Utilize the product experience: Adaptability, Capability, Manageability, Reliability and Usability, and the customer experience in TCO/ROI and Validation. 
7. Evaluate and select the technology properly.
Weight the categories in the technology evaluation criteria to reflect your organization’s priorities to determine the short list of vendors and products.
8. 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. 

The Findings

All of the products we evaluated are feature-rich, but not all the capabilities offered by a software provider are equally valuable to types of workers or support everything needed to manage products on a continuous basis. Moreover, the existence of too many capabilities may be a negative factor for an enterprise if it introduces unnecessary complexity. Nonetheless, you may decide that a larger number of features in the product is a plus, especially if some of them match your enterprise’s established practices or support an initiative that is driving the purchase of new software.

Factors beyond features and functions or software provider assessments may become a deciding factor. For example, an enterprise may face budget constraints such that the TCO evaluation can tip the balance to one provider or another. This is where the Value Index methodology and the appropriate category weighting can be applied to determine the best fit of software providers and products to your specific needs.

Overall Scoring of Software Providers Across Categories

The research finds Informatica atop the list, followed by IBM and Microsoft. Companies that place in the top three of a category earn the designation of Leader. Informatica and Oracle has done so in five categories; Alation, Databricks and Microsoft in two; AWS, Google Cloud, IBM, Qlik and SAP 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 a higher weighted performance to the axis in aggregate of the five product categories place farther to the right, while the performance and weighting for the two Customer Experience categories 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 places software providers into one of four overall categories: Assurance, Exemplary, Merit or Innovative. This representation classifies providers’ overall weighted performance.

Exemplary: The categorization and placement of software providers in Exemplary (upper right) represent those that performed the best in meeting the overall Product and Customer Experience requirements. The providers rated Exemplary are: Alation, Amazon Web Services, Collibra, Databricks, Google Cloud, IBM, Informatica, Microsoft, Oracle and SAP.

Innovative: The categorization and placement of software providers in Innovative (lower right) represent those that performed the best in meeting the overall Product Experience requirements but did not achieve the highest levels of requirements in Customer Experience. The providers rated Innovative are: Alibaba Cloud and Huawei Cloud.

Assurance: The categorization and placement of software providers in Assurance (upper left) represent those that achieved the highest levels in the overall Customer Experience requirements but did not achieve the highest levels of Product Experience. The providers rated Assurance are: Qlik and Solace.

Merit: The categorization of software providers in Merit (lower left) represents those that did not exceed the median of performance in Customer or Product Experience or surpass the threshold for the other three categories. The providers rated Merit are: Ataccama, Atlan, Confluent, Hitachi Vantara, Precisely, Quest Software, Rocket Software, SAS Institute and Syniti.

We warn that close provider placement proximity should not be taken to imply that the packages evaluated are functionally identical or equally well suited for use by every enterprise or for a specific process. Although there is a high degree of commonality in how enterprises handle data governance, there are many idiosyncrasies and differences in how they do these functions that can make one software provider’s offering a better fit than another’s for a particular enterprise’s needs.

We advise enterprises to assess and evaluate software providers based on organizational requirements and use this research as a supplement to internal evaluation of a provider and products.

Product Experience

The process of researching products to address an enterprise’s needs should be comprehensive. Our Value Index methodology examines Product Experience and how it aligns with an enterprise’s life cycle 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, which are flawed since they do not represent an enterprise’s requirements but how the provider operates. As more software providers orient to a complete product experience, evaluations will be more robust.

The research results in Product Experience are ranked at 80%, or four-fifths, of the overall rating using the specific underlying weighted category performance. Importance was placed on the categories as follows: Usability (10%), Capability (25%), Reliability (15%), Adaptability (10%) and Manageability (20%). This weighting impacted the resulting overall ratings in this research. Informatica, IBM and Microsoft were designated Product Experience Leaders. While not Leaders, Databricks and SAP were also found to meet a broad range of enterprise product experience requirements.

Many enterprises will only evaluate capabilities for workers in IT or administration, but the research identified the criticality of Usability (10% weighting) across a broader set of usage personas that should participate in data governance.

Customer Experience

The importance of a customer relationship with a software provider is essential to the actual success of the products and technology. The advancement of the Customer Experience and the entire life cycle an enterprise has with its software provider is critical for ensuring satisfaction in working with that provider. Technology providers that have chief customer officers are more likely to have greater investments in the customer relationship and focus more on their success. These leaders also need to take responsibility for ensuring this commitment is made abundantly clear on the website and in the buying process and customer journey.

The research results in Customer Experience are ranked at 20%, or one-fifth, using the specific underlying weighted category performance as it relates to the framework of commitment and value to the software provider-customer relationship. The two evaluation categories are Validation (10%) and TCO/ROI (10%), which are weighted to represent their importance to the overall research. 

The software providers that evaluated the highest overall in the aggregated and weighted Customer Experience categories are Databricks, Microsoft and SAP. These category leaders best communicate commitment and dedication to customer needs. While not a Leader, Oracle was also found to meet a broad range of enterprise customer experience requirements.

A few software providers we evaluated did not have sufficient information available through websites and presentations. While several have customer case studies to promote success, others lack depth in articulating commitment to customer experience and an enterprise’s data governance journey. As the commitment to a software provider is a continuous investment, the importance of supporting customer experience in a holistic evaluation should be included and not underestimated.

Appendix: Software Provider Inclusion

For inclusion in The ISG Buyers Guide™ for Data Governance in 2024, a software provider must be in good standing financially and ethically, have at least $50 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 customers. 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 Governance enables enterprises to ensure data is cataloged, trusted and protected, improving business processes to accelerate analytics initiatives while supporting compliance with data privacy and security policies as well as regulatory requirements.

To be included in this Buyers Guide requires functionality that addresses the following sections of the capabilities document:

• Configuration
• Data catalog
• Data lineage
• Data stewardship
• Real-time data governance
• AI

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 governance products 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

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.”