Workday has over 19,300 employees in offices across North America, EMEA, and APJ. Workday’s customer list comprises over 11,000 organizations across a diverse range of industries, including more than 60% of the Fortune 500 companies.
With Workday recently being in the news due to a data breach. I thought it prudent for us to discuss data governance.
So, what is a good definition of data governance?
Data governance is a set of procedures or guidelines which detail how data is to be managed, accessed, and used.
Now, while that definition may sound like an abundant bucket of corporate speak, allow me to be clear. This is a very important subject, and business leaders need to think about it critically.
If a corporation wishes to have all of the benefits of storing as much data as they can. Then they should also understand their responsibilities in regards to that data.
Good data governance involves much more than just avoiding data breaches. Here is a small list of reasons as to why data governance matters.
Improved Decision-Making: The only thing worse than no data is bad data. By having guidelines and procedures in place to ensure the reliability of data you store and utilize, you can be confident in the decisions that you make.
Reduced Costs: Good data practices eliminate rework, errors, cleanup, etc. Data analysts and engineers are expensive. Having them waste their time on cleaning up poorly managed data is a waste of money.
Enhanced Compliance: Good data practices can help you meet regulatory requirements…(GDPR, CCPA, HIPAA, ISO, etc.) In many industries, this is not just a “nice-to-have feature.” It’s a necessity.
Increased Operational Efficiency: By having documented procedures on how to share data, you can streamline the process of making it accessible to those individuals who need it and in the format which they require.
If you need help building a good data governance framework for your organization. Here is a small 10-step checklist for you to utilize.
Secure Executive Sponsorship: Without buy-in from the top, this will fail. You need to have a champion that is willing to dedicate time and resources to building a strong data governance framework. Most often, these procedures will be created in-house and require individuals to be rerouted from their normal duties. Without executive leadership leading this charge, most of these individuals will get pulled from this project before it’s completed.
Define Data Governance Goals & Scope: Know what you trying to achieve. Start small and stay focused.
Identify Key Data Domains: (e.g., Customer Data, Product Data, Financial Data). Prioritize based on business impact.
Assign Data Owners & Stewards: Identify who is accountable for the accuracy and quality of each data domain.
Develop Data Policies & Standards: Be certain to cover the following areas; Data Quality, Data Security, Data Access, etc.
Establish Data Quality Rules & Metrics: How will you measure data quality? Set clear thresholds. Remember, ambiguity is going to be your enemy in this area.
Implement Data Security Measures: This is a big one. Organizations need to spend time on this area by doing research and deciding on what make sense for their organization.
Create a Data Catalog & Glossary: Make data understandable and discoverable across the organization. Also, you need to ensure that you create processes which will allow future data to be cataloged and searchable in the future.
Monitor, Evaluate, and Adapt: Data Governance is not a one-time project; it’s an ongoing process. Regular audits, feedback loops, and adjustments are essential.
As you get started down this road, you’ll realize how large this behemoth can become. But just remember, perfection is the enemy and improvement is the goal.
Jonathan Adams
August 21st, 2025