Data Governance Best Practices for Modern Businesses
Every business relies on data to provide key insights into the most important aspects of financial and operational health. Many organizations face a need for better quality data and more efficient ways of accessing and leveraging that data to their advantage. Poor data quality and weak data governance often prevent organizations from harnessing the power of their data. As businesses seek to stay competitive, it’s critical they establish robust data governance frameworks and invest in tools and processes necessary to ensure data quality, accessibility, and usability to drive informed, strategic decision-making.
When dealing with business data, we naturally focus on the data and what it means to us individually. Before diving into data usage and visualization, it's important first to consider what the data represents as a whole. This is where the concept of data governance comes in. As a framework that defines how your organization uses data, determines what is meaningful, and establishes how to maintain that data, a data governance policy is an essential starting point. Starting with governance provides a platform for all subsequent components to build on and forces us to think about decisions and practices that will become more important later in the process. The lack of even minimal governance can cause an analytics project to fail.
Data Governance Initiatives
At a minimum, your data governance policy should answer the following questions:
What data do you care about? (Data Classification).
What software and hardware systems hold this data? If there are multiple systems, which ones are the source of truth? (Data Lineage).
What are the restrictions on the visibility of data? (Data Security).
How do you make sure that your data is clean and consistently entered or extracted? (Data Hygiene).
What is the sensitivity level of your data? For example, does it contain Personally Identifiable Information (PII) or Protected Health Information (PHI)? (Data Privacy and Classification).
What are your privacy responsibilities related to that data, and what are the impacts if you lose control of that data? (Data Privacy).
How long is data valid? What happens to it when it’s no longer valid? (Data Retention).
What decisions can people in the organization make using your data? (Data Policy).
How does the organization calculate performance indicators? (Data Policy).
Considering these questions, it’s clear to see how they will become important to other parts of the process. For example, it’s hard to create a dashboard of key performance indicators (KPIs) if you haven’t already determined what they are and how to calculate them. You will return to these questions many times while building and using your business intelligence platform, which is why they are the perfect starting point.
Data governance fundamentally reflects your organization’s values and helps define its thinking around the meaning and management of data. We recommend starting with collaboration amongst leaders in the business to understand what’s important to each group. You’ve likely done this already, perhaps informally, but every organization has both spoken and assumed rules and values around how data are used, who can see what data, and how KPIs are calculated. The imperative here is to formalize that, gain agreement on it, and put it in writing. Revisit it regularly and keep it up to date as you would an employee handbook or procedures manual.
Data Governance Practices
Take some time to consider how various parts of your policy interact. For instance, if you set a data retention period of three years, how does that affect KPI calculations? If you have data privacy guidelines, how do they influence data security?
This can be a lot to tackle, but it’s crucial that these items be addressed. The good news is that you don’t need every detail figured out from the beginning. Every data governance policy grows and changes over time, and it may be perfectly fine to consider it a work in progress. Start with a basic plan, and let it inform your work moving forward.
For more help with data governance, lean on the experts at Clark Schaefer Consulting.
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