Data governance; is an aspect of the digital environment essential to becoming data-driven. Data governance gives organizations knowledge about their data, and the insights to optimize its value. If you have ever said, “Where is the data I need?”, “I don’t know what the data is in this column?” or “Why does it take so long to onboard someone to the data team?”; This blog will answer these questions through a quick run-down on what data governance is, why it is essential, and who should be tasked with it. 


  1. Data governance is a process that is a part of any organization’s maturation with data enablement, which leads to all employees speaking the same language about the data. Organizations often focus on data governance when migrating data from legacy systems to an enterprise data warehouse. When done correctly, it gives employees the ability to contribute, find the knowledge of key data elements found throughout the enterprise, and build trust in the data, all while reducing unnecessary rework. 
  2. Every company has some form of data governance. Most early stages include notes about reports, tables, databases, and sources. Data governance aims to expose and connect the siloed knowledge about the data – known as metadata – held by departments or small groups within the organization. It also allows organizations to separate valuable information that can enable business innovation and advantage. 
  3. There’s a wide range of digital tools for data governance. If there is a small volume of data or just a few people using the data, companies can begin their data governance work in Excel or SharePoint. For larger organizations, platforms like Collibra and Alation are purpose-built to enhance and accelerate data and have critical features for reaching mature levels of data governance. 
  4. Data governance has a very large return on investment regarding business benefits. By standardizing the knowledge about data and the way employees refer to it, companies gain: 
  • Reduced risk of inaccuracy in data use and reporting
  • More efficient data use
  • Enhanced ability to meet security and compliance requirements
  • Faster onboarding of new hires with data roles in both IT and Operations
  • Faster IT ticket resolution and troubleshooting


Effective data governance approaches fall into two categories. With bottom-up data governance, the organization identifies a team of employees who use the data and understand the value of data governance. Ideally, the team would include the analysts writing the reports and a sponsor who keeps the process moving. The accuracy of the data and maintenance of the content, while allowing others the ability to comment, question, and validate, is crucial to this approach. 

The team will use an iterative process that starts with prioritizing and defining the data elements. As they move along, they may add:

  • Data lineage (where is it in the source system)
  • Listing of the front-end apps that use the data element
  • Business rules that apply to the data element
  • Transformation logic (a record of changes from the source system to the data warehouse)
  • The subject matter expert (SME) for each critical data element ( an individual who knows the most about the data or is responsible for addressing issues involving the data). 
  • Notes on data quality 

This process is where data governance assists with compliance. In healthcare companies, for instance, certain data elements can be designated as “identifiable” in the data governance system, which cues any employee to use that data according to compliance requirements.

With top-down data governance, an organization hires or designates a Chief Data Officer to lead the initiative.


A good place to start a data governance journey is to identify subject matter experts and ask them to share documentation about the data they use to see how informative it is. After this, take a more technical approach to connect the data warehouse(s) with a metadata management tool, and after exporting the column and table descriptions, evaluate gaps between that and the subject matter expert’s understanding of the data. 

The more mature your knowledge is about your data, the faster you can use and grow from it, making data governance a core element for businesses. Wherever your organization is on the road to becoming data-driven, TESCHGlobal has individuals such as; data engineers, data analysts, and subject matter experts experienced with data governance who can assist and ensure your data is an asset to your organization.