Data Intelligence foundations for federal agencies

Why does Data Intelligence for federal agencies matter?

In January 2019, President Trump signed the “Evidence Act,” a law that requires Federal Agencies to instate a data catalog and appoint a CDO as a means of providing better data-driven results to the American people. The “Evidence Act” is a response to many of the challenges that government agencies face such as siloed data due to legacy technology architecture and various classification levels which ultimately makes data sharing difficult. While large commercial corporations face similar problems, some federal agencies face additional challenges due to the security complexity of the data needed to accomplish the mission. The government also struggles to share data across agencies, which can lead to threats to our national security. In fact, after 9/11, the government created the United States Department of Homeland Security to facilitate, among other things, the sharing of information across agencies that are charged with protecting the homeland. However, despite these efforts, the sharing of data is still an immense pain point today. 

So how do government agencies alleviate this pain?  

Government agencies must invest in Data Intelligence so that they can find, understand, and use their data in the right way. More specifically, government agencies must first lay the foundation of data governance with a business glossary, domain modeling, and data sharing agreements. 

  1. A business glossary provides a common language across the agency and the entire government. This is crucial in the government when data is used to make major decisions that could impact the country and the world. For example, if there is not a unified definition of “Person” within an agency key decisions could be based on incorrect data like social services or even the census. The business glossary prevents this problem and helps ensure that internal agency teams and interagency collaboration are on the same page when making data-driven decisions. 
  2. Data domains are the next step in laying the foundation of data governance. Data domains create a common definition of key terms that are mapped back into the business glossary. They are the nouns that drive your business. In the case of a large retail company, their data domains may be employees, products, customers and locations. However, in the case of government agencies, agencies are concerned with a wide range of domains such as agriculture, climate, health, immigration, and national security. Similar to the benefits of a business glossary, domain modeling ensures consistency across the government. 
  3. Establishing data sharing agreements is probably one of the most important steps in your data governance journey. Today in the Federal Government, there is no unified system in place for how to share information across agencies. As a result, many agencies have their own system or process to initiate data sharing with other agencies. Unfortunately, because this process is not generally known throughout the agency, internal organizations repeat processes unnecessarily. Creating data sharing agreements solves this problem by initiating a request and approval process for internal and external data sharing and usage. 

Now that you laid the Data Intelligence foundation, what’s next? 

The next step to becoming a data-driven agency is to establish a data catalog within your organization. A governed data catalog helps agencies discover the data they need, understand its meaning and context, trust it is accurate and compliant, access the data for immediate use, and collaborate and contribute within your agency and the broader government. A data catalog helps solve the issue of siloed data by creating a central repository to “shop for data.” It enables data transparency and data democratization within the organization, thus breaking down silos. 

That being said, you may be thinking, I don’t want everyone in the agency to have access to all data. Luckily, with a governance foundation already established, you don’t need to worry. This ensures that your data is secure and that people within the agency have to go through the appropriate request process to access certain data, thus making sure that sensitive data stays safe and secure. 

What are the benefits of Data Intelligence for Federal Agencies? 

As federal agencies look to do more with data, it is important to think beyond the what and how (data governance and data catalog) and focus on the why. Why should federal agencies invest in a Data Intelligent solution? Because it creates the opportunity to

  1. Enable data-driven decision and policymaking 
  2. Reduce the time required to find data or identify golden sources 
  3. Improve citizen-facing services based on valuable data insights 
  4. Provide data to stakeholders, academia, partners for innovation, security, or the mission.

These four best practices add value to the organization and support security, regulation, and compliance efforts such as, protecting PII and other sensitive information, complying with FISMA, NIST, and cybersecurity standards. It also helps with complying with regulations, policies, and laws including the new “Foundations for Evidence Based Policy Making Act.” Ultimately, solving Data Intelligence for federal agencies will help agencies do their jobs both effectively and efficiently. It will decrease time to insights for policy making and other important decisions and will curb confusion while reducing duplicated efforts across the government.  It will not only help eliminate data silos but also increase communication and collaboration across agencies to ensure the best results for the American people.

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