Solution Briefs

This solution brief shares best practices for how government agencies can derive value from their data lake investments.

Below is an excerpt from the brief. To read the full brief, [click here]

Government agencies are under mounting pressure to extract value from the ever-expanding troves of data they generate, collect and store. When properly used, data enables better decision-making and reporting; seamless, timely and personalized constituent experiences; and intelligent automation.

Moreover, in light of the Evidence-Based Policymaking Act,1 Congress proved how much the government could benefit from using data evidence to create policies and inform programs. To ensure adherence to the Act, agencies will need to establish a comprehensive data management strategy enabling them to easily account for all the data assets and metadata (data about data) created by, collected by, under the control of, and maintained by each agency. This will allow better intra- and cross-agency collaboration (sharing of data) and increase data literacy (understanding of data).

While agencies have invested in data lakes as a step toward storing, processing, analyzing and sharing large amounts of data, many have encountered challenges with widespread data lake adoption and actually putting their data to work. They’ve found that data — and their investments in data lakes — cannot return full value if users cannot easily find and understand the data they need or ensure the data is trustworthy and of high quality. In a highly regulated environment like government, data lake adoption requires rigorous checks and balances to ensure data is easily findable, traceable and that it meets the highest data quality thresholds to derive value from it in a timely manner.

Data lake management and adaptive governance unlocks the value of data by making data ecosystems accessible, transparent and trustworthy for all users – including data producers, data scientists and data consumers – which allows them to connect data to various use cases and make information actionable. This in turn fosters greater data lake adoption across departments, agencies and jurisdictions.