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        David Menninger's Analyst Perspectives

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        Good Data Governance Improves Business Processes

        Many organizations invest in data governance out of concern over misuse of data or potential data breaches. These are important considerations and valid aspects of data governance programs. However, good data governance also has positive impacts on organizations. For example, I have previously written about the valuable connection between the use of data catalogs and satisfaction with an organization’s data lake. Our most recent Analytics and Data Benchmark Research demonstrates some of the beneficial links between data governance and analytics. In this Perspective, I’ll share some of the correlations identified in our research.

        Data governance includes many elements. First and foremost, data governance is not a technology. It’s a set of processes and policies designed to ensure the accuracy, quality and appropriate stewardship of an organization’s data. In this day and age, data governance should always be supported by technology, but the organization’s policies provide the principles by which an organization’s data will be managed. A good data governance program includes processes for inventorying data assets in a data catalog, ensuring data quality, managing master data, and restricting access to and use of data. The program also needs to codify and publish the organization’s policies so they are known and understood.

        Our research explored how adequate an organization’s technologies were for various aspects of data management. Analytics capabilities were identified by participants as the most adequate, and event streaming and unstructured data management were considered least adequate. In the middle were a number of data related activities such as data integration and master data management. For purposes of this Perspective, I’ll focus on the broad category of data governance.

        Ventana_Research_Benchmark_Research_Analytics_14_Adequacy_of_Data Management_20211025 (1)If we contrast those organizations that reported data governance technologies were completely adequate with all other organizations, we see that satisfaction with analytics is significantly higher: 49% compared with 26%. We also asked organizations if analytics have improved business processes. Nearly 6 in ten (59%) organizations with completely adequate data governance technologies reported that analytics had significantly improved activities and processes, compared with just over 4 in ten (43%) of all other organizations. Looking at one other measure which some consider the holy grail of analytics — whether or not an organization can provide self-service analytics — we see similar results. Nearly two-thirds (64%) of organizations with completely adequate data governance technologies are comfortable allowing business users to work with data that has not been prepared by IT, compared with 4 in ten (41%) organizations reporting less adequate technology.

        It’s important to point out that correlation is not causation. Logically, it makes sense that good governance can help improve analytics outcomes. For example, good governance helps ensure data quality, and better quality data is likely to lead to better decisions and therefore more improvements in business activities and processes. While we can’t say for certain that implementing good governance technology causes these outcomes, if your organization expects to be one that enjoys these benefits, you should also expect to make investments in data governance technology.

        We continue to research data governance more deeply in our Benchmark Research project. Participate in the research and gain access to related research. You can also subscribe to our Analyst Perspectives and get notified when new viewpoints are available.

        Regards,

        David Menninger

        David Menninger
        Executive Director, Technology Research

        David Menninger leads technology software research and advisory for Ventana Research, now part of ISG. Building on over three decades of enterprise software leadership experience, he guides the team responsible for a wide range of technology-focused data and analytics topics, including AI for IT and AI-infused software.

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