Data is at the center of every mission and task in government, from policymaking, to enabling the warfighter on the battlefield, to streamlining information sharing for national security. Dealing with large amounts of government and partner data efficiently and securely requires new strategies for containing, controlling, securing, and using these diverse data sets.<\/p>\n\n\n\n
Yet, as public sector leaders increasingly use data to achieve their missions, chief data officers, chief information officers and chief information security officers are faced with cultural and workforce challenges that can hinder their journey towards becoming a more data-driven government. With the renewed focus on digital transformation across agencies, data can and should be used to drive government innovation. But how can government leaders fully exploit their ability to innovate with these challenges constantly looming?<\/p>\n\n\n\n
People, process, and technology must be properly aligned to affect real cultural change. IT and data engineering teams should not build systems and platforms solely for the sake of IT. A \u201cbuild it and they will come\u201d mentality will not move agencies toward having a data-driven culture with active engagement in using data to derive valuable insights for decision-making.<\/p>\n\n\n\n
So, how can senior government leaders organically cultivate a real data-driven culture? How can they remove data silos and other barriers that hamper their ability to make the right data available to all federal employees when they need it? Here are a few tips to consider:<\/p>\n\n\n\n
Agencies know enough about their data to know where the challenges and pain points are \u2013 and often, the most glaring issues are felt across departments. Therefore, prioritizing a solution that solves shared pain points will have a greater impact across the entire agency. If the IT\/data team can use cloud technology to address a common pain and frustration, they will be better able to secure buy-in for a cloud migration from all the data stakeholders, remove barriers to data, and step-by-step, start to break down data silos.<\/p>\n\n\n\n
Don\u2019t boil the ocean by thinking about the entire environment. Instead, prioritize the biggest pain point(s) and tackle those first to get more immediate results. Start with the problem, create a tactical plan, and build out from there.<\/p>\n\n\n\n
Transformation projects not only require the right people \u2013 they also require the right mix of people. To build a truly effective data-driven culture, agencies need to build a workforce that is holistically prepared to execute data initiatives.<\/p>\n\n\n\n
Data scientists and data engineers are now becoming common career options in government due to the essential skill sets these roles require. Businesses and government agencies are vying to attract the same talent\u2014data scientists, data engineers, data analysts \u2013 and in doing so are further solidifying that data is at the center of the business and mission.<\/p>\n\n\n\n
In many agencies, analyst teams have been pigeon-holed into using the same tools to build the same set of analytical results for many years. It\u2019s easy to say, \u201cthat\u2019s how we\u2019ve always done it and it works,\u201d but to truly harness the power of their data, agencies must pivot and invest in upskilling their workforce. Agencies should focus on being more proactive with the questions asked of data, and managers are responsible for identifying people who are interested in being upskilled. The federal workforce must be focused across skill sets on how data can help the government achieve its mission.<\/p>\n\n\n\n
A big hurdle for data owners to overcome is recognizing that data can and should be shared. For many IT managers, there are no gray areas \u2013 either people are allowed access to data, or they are not. However, today\u2019s technologies allow for nuanced access control frameworks that give data owners granular control over what and how to share data. Using techniques like privacy controls, data masking, and redaction, data access does not have to be binary in order to be secure.<\/p>\n\n\n\n
The agencies that execute this most successfully will be those that translate rules into policy at the data set level and automatically apply them at the speed of mission need. For example, the Department of Defense\u2019s workforce has security clearance levels that determine who can access specific data. But even defense agencies struggle with how to automate and enforce data access policy using clearance information.<\/p>\n\n\n\n
Technology has advanced to the point where agencies can get fine-grained access control that makes context-aware policy enforcement decisions at query runtime. This approach puts the right data into the hands of the analysts who need it, without having to make a binary, role-based decision at the data set level. Data then becomes the driver of mission, action, and intelligence, instead of being locked up in silos.<\/p>\n\n\n\n
Being truly data-driven requires managers to ensure the outcomes they are looking to achieve align with mission objectives. It\u2019s time to move away from the \u201cbuild it and they will come\u201d mentality driven by technology decisions. Instead, agencies should evolve to a data-driven culture by changing the mindsets and approaches of the people that are there today. Using mission requirements and hard questions to drive the implementation and adaptation of data platforms will demonstrate the art of the possible and prove how everyone \u2013 from data engineers to analysts and consumers \u2013 can benefit from proper access to and proactive use of data.<\/p>\n\n\n\n
Nancy Patel is vice president and general manager of public sector at Immuta, a provider of data privacy and access controls services<\/i>.<\/p>\n\n\n\nHave an Opinion?<\/h2>\n\n\n\n