Breaking down data silos

After 9/11, the U.S. federal government created the Department of Homeland Security (DHS) to combine all or part of 22 different federal departments and agencies into a unified, more effective and integrated body, creating a strengthened U.S. security enterprise with a mission, stated in part, “to ensure a safe, secure, and prosperous Homeland.” (See dhs.gov.) The DHS founders recognized that gaining access to multiple data sources provides better, more insightful information for more effective decision-making. Likewise, in cybersecurity, organizations and government agencies often collaborate in data-sharing consortiums to share intelligence with many different stakeholders and generate the right level of situational awareness for organizations to defend themselves against cyber threats.

Ten years ago, the phrase “big data” was all the rage with software and technology companies. That term is no longer relevant because today’s organization commonly deals with large amounts of volume, variety and velocity (aka, big data, both unstructured and structured). The U.S. Department of Justice (DOJ) 2023 compliance guidance document, “Evaluation of Corporate Compliance Programs,” asks prosecutors when investigating a company to determine if “compliance and controls personnel have sufficient direct and indirect access to relevant sources of data to allow for timely and effective monitoring and/or test of policies, controls and transactions?” (See “Evaluation of Corporate Compliance Programs,” DOJ, Criminal Division, updated March 2023.)

So, knowing what we do about the need for data sharing and access to multiple data sources, why do we still often see organizations miss critical fraud risks when the information to prevent and detect it was available? More often than not, it’s because different systems within an organization weren’t talking to each other. It’s time to break down these data silos once and for all.