In our previous article about data governance, we revealed three basic concepts to put you and your business on a path to a single source of truth. Now that we’ve established that business leaders must take a hands-on approach to their data, it’s time to lay the groundwork for a data governance program that can’t fail.
Let’s have a quick refresher: A data governance program establishes guidance for data infrastructure and technology; policies and procedures for managing, securing, and accessing data; and roles and responsibilities for the accuracy and trustworthiness of the data (in other words, data quality). It ensures the entire organization is on the same page in terms of managing this very important business asset.
To prime your program for success, we’ve formulated three simple questions that, when acknowledged and answered, can effectively calibrate your fledgling data governance plan to run as smoothly as possible.
Although achieving a high standard of data quality is the ultimate goal of data governance, it’s not the only outcome that matters. Consider the perspective of data scientists: These specialized technicians spend an inordinate amount of time sorting through unprepped (i.e., ungoverned) data to plug into their machine-learning models. Now, imagine if your valuable information was prepped and ready before it reached the data science team or even business users with a novice’s understanding of analysis. The time savings and increase in speed to market could be plentiful.
It may seem like splitting hairs, but time spent on preparation can lead to missed opportunities to make sales or introduce products at the most opportune moment. If a project accompanied by poorly governed data is handed off to your data science team or end users, they may not be able to proceed until those issues are cleaned up. Well-governed data equates to more time for these specialized technicians to make important decisions.
Make sure your team has access to a data catalog that contains all relevant information. By cutting down on manual input and clerical work, you give users enough moments of clarity to extract insights from well-defined, agreed-upon data. Using sales as an example, imagine if your team hasn’t agreed on what constitutes a completed sale. Is it complete when a contract is signed or only after a customer is onboarded and in the system? These are conditions that must be agreed upon and accounted for in a data catalog.
That’s not an outlier use case. Functions ranging from finance and human resources to marketing, customer service, and R&D all have their own chances to solidify data cohesion and uniformity. You shouldn’t leave that information up in the air for your data science team to parse through. By properly governing your data and defining these terms, there’s no disagreement—and far less wasted time.
At Wavicle, we believe that data governance should never be completely siloed in an organization’s IT department. The concepts of usability, accuracy and security across data touch every aspect of the enterprise. For that reason, it’s far more effective for all business leaders to take a hands-on approach to the data they need to make decisions. That being said, most processes can benefit from having a dedicated leader at the top of the pyramid. To ensure that all data governance efforts at your company run as smoothly as possible, you may decide that the buck needs to stop somewhere more specific to maintain accountability.
So, who should take on the title of Resident Data Governance Expert? There are many schools of thought on this, and the answer could be any number of C-suite roles, from CISOs and COOs to even more financial-minded leaders such as CFOs and CROs. The profound way data governance influences every business function means that perspectives beyond those of data experts have bearing on the success and adoption of this mindset.
But when choosing the right leader, the defining quality is quite simple: Your ideal champion will have the willingness to understand how the framework of data governance helps end users solve problems, not to mention the attention to detail to keep things organized. It’s through their passion that all the catalogs, quality scorecards, leakage prevention strategies, business glossaries, and other organizational approaches to data assets create a positive ripple effect across the enterprise.
Data governance provides infrastructure, policies, and processes that maintain availability, usability, integrity, and security—a very tall order, indeed. With proper setup and automation, it can do wonders. But if you don’t have a clear understanding of the key disciplines involved in data governance—namely, master data and metadata—your program may fail to improve outcomes for your business.
We’ll start with metadata, which is sometimes referred to as “data about data.” To ensure sound data governance, organizations must manage the creation, storage, integration, and control of metadata. This enables businesses to develop an understanding of terms and usage, creating a common language for business. It also increases the value of information by providing context for more effective decision-making, among many other valuable outcomes.
But let’s say not everyone on your team thinks of metadata in the same way. Imagine a group of analysts who take ownership of their metadata, but in a way that aligns with their day-to-day work instead of the overall goals of the company. This could potentially lead to small, localized successes for them, but it could also confuse virtually everyone else at the company looking to use information compiled by the team.
As you can see, there are a ton of moving parts to consider when planning your own data governance program. But by asking these three key questions, you and your business have a much better chance of calibrating a program that will find success in the long term. With preparation and communication, you can put an entire organization in a prime position to start governing data the right way.
Ready to begin your data governance journey? Wavicle can help answer all these questions and more.