Data Governance: The Final Step to Gaining Valuable Business Insights

April 13, 2023 Rasvan Grigorescu

This is the final blog in a seven-part series on generating data insights to drive business decision-making. In our first blog, we discussed why data management is important, followed by Step 1 in the process—data ingestion; Step 2—data transformation; Step 3—data modeling; Step 4—data visualization and analysis; and Step 5—data collaboration. In this blog, we present the final step—data governance.

After you successfully complete the first five steps of your journey to manage your data so it generates valuable business insights, you’re ready to realize the true value of the information. You’re linked to your vital data sources and can transform that data into helpful reports and dashboards.

To ensure your journey continues to be a success, you now need to make sure all that data is used in the right way. That’s where five governance components come into play:

#1 – Create a Unified Map of Data Across Your Data Estate

If users don't know where data is and the types of information that various sources provide, the data is hard to use. By creating a data map, you can inform users about all data sources and sets of reports across your on-premises, cloud, and SaaS sources.

The map needs to capture four types of metadata so users can get a clear sense of the data:

  • Technical metadata communicates the data schema and data types (numeric, text, dates) as well as the column titles of each table.
  • Business metadata is often generated from SQL table data sets (such as customers, products and invoices) and includes a glossary of terms to define exactly what each term means and its relevance to the organization.
  • Semantic metadata pertains to data sources. Where is the data coming from and how is the data classified?
  • Operational metadata displays data activities, such as how and when the data was created and when the data has been viewed.

Data classification is particularly important to regulatory compliance. This is how you label sensitive data, such as personally identifiable information. By classifying data, you can prove you’re aware of where you’re storing it and demonstrate how you protect it.

#2 – Make Your Data Discoverable

With all the data sources your business taps into and the many reports and dashboards you produce, it can be challenging for users to locate specific information. You can overcome this challenge by providing a data catalog that lets users browse and search for data using technical or business terms.

Ultimately, the data discovery process provides users—such as data scientists, engineers, and analysts—

with the data they need for analytics and to build machine-learning algorithms. They may know how the business operates but finding the specific data they need to solve business problems may be difficult.

Another key aspect of discovery is data lineage, which traces the journey of data from its initial source through its transition to reports and dashboards. Understanding where data comes from is particularly important when the source is a rarely-used legacy system. Knowing the source is also important when troubleshooting data inconsistencies.

#3 – Measure Data Usage

To determine the ROI of your data insights projects, you need to know who is using your data outputs, how often, and how those insights help them make decisions. You also want to be aware of how well your data sources and data types work so you can adjust where necessary.

If you find an under-utilized data source, then the question becomes…Why? Is the data relevant? Is the data inventoried and discoverable? Is it categorized correctly? Is there someone assigned to curate the data? A breakdown in any one of these areas can cause a data source to not deliver value.

Your company may get excited about a data source and ask for lots of reports. But after the excitement fades and the reports are generated, if nobody uses those reports, you do not get a return on your investment.

#4 – Share Data Without Creating Duplicates

Centralizing data—rather than isolating it in silos—not only makes the data easier to share, but also prevents duplicates and conflicting versions. Sharing is the key to making insights more valuable; the more people who know about the data, the more decisions and workflows the information influences.

Also think about sharing data outside of your organization, perhaps with customers, partners, and market analysts. While the restrictions on access and what people can see will be more limited, sharing with external parties can also be valuable. You can collaborate to create synergies that lead to new products and services.

#5 – Control Access

Here’s where you consider who has access to which data sets so that you share the right data with the right users. This component involves setting the policies that allow data engineers to provision access to data assets based on approvals by data owners.

The policies you set for controlling access will need to conform to your internal guidelines, and for any sensitive data you handle, you will need to comply with pertinent regulations. Some regulations may require you to monitor compliance and review your policies regularly to ensure they continue to conform. From time to time, you will also need to hire an independent third-party auditor to attest to your compliance.

A Handy Tool for Managing Governance

Microsoft Purview offers a handy tool for managing each of the five governance components with a range of solutions to keep your organization’s data safe and to integrate data governance with systems that handle information protection, risk management, and compliance. Key features include tools for data mapping, data cataloging, data state insights (usage metrics), data sharing, and data policy.

Leveraging a tool like Purview is vital because when planning a data insight implementation, enterprises sometimes put governance aside and then worry about it after completing the project. But it’s critical to begin your journey with governance in mind. Well-managed governance is the key end state, and you want to make sure you take the right path to get there.

Everybody wants reports to generate insights. But once the initial enthusiasm wanes, the data officer might realize, “We paid for developing this report six months ago, and today, nobody is using it.”

It’s not enough to simply produce the insights—you need to be sure the business gets value from the insights. And that’s where governance pays off.

If you need help managing your company’s data to generate valuable business insights, Western Computer is here to help. Contact us to today learn more about our Microsoft solutions and how they can help you aggregate, analyze and govern your data.

About the Author

Rasvan Grigorescu

Senior Data Architect Rasvan Grigorescu has more than 20 years of leadership and technical experience in driving business value from data.

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