“Data is the new currency.” Chances are you've heard this before. Put simply, data-driven organizations outperform their competitors and are 23 times more likely to acquire customers. The question becomes: How can your organization leverage data — consistently, accurately, and safely — to make smarter business decisions each day? This is where data governance comes into play — and data stewards step in to ensure businesses keep up with established data principles, rules, and standards.
Once data governance processes are in place, it's easy to assume they'll run themselves. But even with a robust data quality or master data management (MDM) platform, you'll need a person (or people) to enforce the principles and processes established by your data governance framework. They will also monitor your data processes, suggest new rules, build systems and mitigate data issues. And they will ensure the quality of your data, master data, and metadata throughout the entire data lifecycle.
In this article, we’ll cover the definition of data stewardship, why it matters, and what are the roles and responsibilities of a data steward within your organization. Let's start by defining data stewardship.
Data stewardship is the collection of practices, processes, and tools that ensure an organization’s data assets are accessible, usable, safe, and trusted. It includes managing and overseeing every aspect of the data lifecycle from creation, collection, preparation, and usage to data storing and deletion. Stewardship ensures that the data has a clear owner or owners responsible for keeping it in good working order. This usually involves establishing a set of principles, procedures, and best practices around how the data is stored and used to promote data quality and integrity.
Data stewardship encompasses:
According to Gartner’s senior analyst, Ted Friedman, "As organizations accelerate their digital business efforts, poor data quality is a major contributor to a crisis in information trust and business value, negatively impacting financial performance." It has become easier than ever for businesses to gather data, but this comes with just as much responsibility as opportunities. In fact, 40% of companies will fail to achieve their business objectives and even lose about 20% of revenue due to poor data quality. These setbacks would likely not occur with an effective data stewardship model in place.