Laying the Foundation for Robust Data Governance

Joey D’Antoni

Published On: August 3, 2021

Categories: Documentation, Data Governance 0

Data governance is a set of responsibilities and processes used to manage your data assets to meet your business needs, security requirements, industry regulations, and data integrity. The MDM institute has an often-quoted and succinct definition of data governance as “the formal orchestration of people, process, and technology to enable an organization to leverage data as an enterprise asset.” It’s an ongoing program, not a one-time project or a software solution, although it usually involves several projects and software applications.

A successful data governance program should ensure your organization:

  • Knows what data you have and where it’s located
  • Is cataloging and sharing data with authorized users
  • Has identified data owners, technical owners, and data stewards for each data set
  • Understands the lineage, quality, and availability of each data set
  • Has agreed on how each data set can be used and by whom, and can verify those decisions are enforced

Data Governance Scope and Benefits

Data governance affects nearly everyone in your organization, since pretty much everyone in the organization uses data. But just as the governance requires participation from everyone in the organization, it can benefit everyone in the organization. Benefits of data governance can include:

  • Reduced cost and time spent on data management and storage
  • Increased trust in and understanding of data
  • Increased speed and effectiveness of data-informed decisions
  • Improved compliance, data security, and privacy
  • Improved transparency and increased value of existing data

Data governance is a broad topic and includes many disciplines. Successful data governance programs become part of an organization’s culture and should involve all uses of data and related processes within the organization.

Figure 1 shows several disciplines commonly identified as key components of a mature data governance program.

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Figure 1: The many disciplines involved in data governance

If your organization is just getting started with data governance, it can be overwhelming. The next sections provide some direction to help you quickly get up and running and achieve some early successes.

Where to Begin

The first step in implementing a data governance program is to get executive buy-in for your project. You need to make data governance not only an IT priority but also a concern for sales, finance, marketing, operations, and other business groups.

Buy-in means having both vocal support and approval of dedicated time and budget. If the promise of understanding the value of your data and working more efficiently doesn’t excite executives, you might want to focus more on the value of compliance. Failure to comply with data privacy laws such as General Data Protection Regulation (GDPR), California Consumer Privacy Act (CCPA), or Health Insurance Portability and Accounting Act (HIPAA) can result in fines, lawsuits, and a damaged reputation. Avoiding those outcomes is often very appealing to executives and can be an impetus for increased data governance maturity.

Form a Council

You will eventually want to form a data governance council. This council should include:

  • Data owners: Decision makers who control the source systems where data resides and who are responsible for access to data under their guardianship
  • Data stewards: Subject matter experts on a data set, data tool, or data process who follow and help enforce data governance policies
  • Technical owners: System administrators, database administrators, and other IT professionals who are responsible for the availability and security of data and related processes
  • Executives and other stakeholders

You don’t need to immediately get everyone together in a meeting. Just start identifying the people in your organization who fit these roles.

Evaluate Your Data Governance Maturity

The next step is to evaluate your current level of data governance maturity. There are several maturity models to choose from, published by organizations such as Gartner, IBM, and Stanford. You’ll want to survey people in different departments and different levels across the organization to get their view of how things are currently working. The group surveyed should include many, if not all, of the people whom you’ve identified as candidates for the data governance council.

A free and fairly simple version of a data governance framework evaluation by Robert S. Seiner is available from The Data Administration Newsletter. This evaluation can be used initially to understand your current status and identify opportunities for improvement. As you move along your data governance journey, you’ll be able to repeat this evaluation and use the results to show progress.

Start Small and Demonstrate Success

It’s often effective to start small with data governance and show early success. Data governance programs can be implemented in an agile manner just like other IT programs. Before asking lots of people to dedicate time and effort, it’s often beneficial to identify one small to midsize project where you can improve data governance and show business value from the outset. Then, have the project team and the executive sponsor publicize the success and impact of the project. This will get people excited about data and improved data governance.

Catalog Data Storage and Access

A common first project is to catalog all the data sources, data repositories, and tools used by a single department or process. You don’t want to try to do this across the entire organization or even a large business unit all at once, as it can be a never-ending undertaking. Keep a small, well-defined scope.

Helping people understand how many places data is accessed and stored, how many times it’s transformed, and the number of people and processes that touch it along the way can be very eye opening. It often leads to realizations that data is duplicated and stored in multiple places, and not all of those places are well secured. Immediate steps can be taken to remove duplicate data, which results in cost and time saved, as well as reduced security risk.

Many times, organizations find multiple people are transforming the same data in similar ways with slight variations, which results in conflicting results and time wasted. Fixing the duplicative processes and the variation in data preparation can result in time saved, increased communication, and increased data quality. Sometimes, cataloging data helps connect people to data sets they were previously unable to locate due to lack of awareness or a communication breakdown. They can show productivity gains or increased job satisfaction after a period of using the new data.

Documenting Data Processes

As you can see, data governance is a large topic, but you can start small to make improvements and get buy-in. Often, documenting data integration and reporting processes is a good place to start.

When you begin researching solutions for documentation and data lineage, look at SolarWinds® Database Mapper. With Database Mapper, you can easily maintain up-to-date database documentation and demonstrate compliance with business rules and data privacy regulations by accurately tracking data lineage. Get started with a demo or free 14-day trial here. See for yourself how it can help you improve data governance in your organization.

Joey D’Antoni is an ActualTech media contributor and a principal consultant at Denny Cherry and Associates, Microsoft Data Platform MVP, and VMware vExpert.