The Federal Data Strategy articulates a goal to “fully leverage the value of federal data for mission, service, and the public good.” But how does a federal agency do so when their data is siloed, inconsistently formatted, and scattered across on-premise and multi-cloud environments?
The answer is to utilize data insights platforms that can span disparate data sources and locations, and correlate data rapidly for insights that enable navigation and course correction of agency missions.
Not all agencies have invested the time and resources, nor possess the skillsets required, to implement such platforms. Managed Platform-as-a-Service (MPaaS) is a way for these agencies to accelerate the journey to unfettered data access.
And not all agencies possess the data engineers and scientists required to tap their data for enlightening insights. Managed Data Analytic Services is a way for these agencies to accelerate their journey to data insights that will fuel their mission’s operation and potential transformation.
Federal decision-makers are looking to maximize their spend on information technology and services to better achieve mission goals and business outcomes. But what data do their analysts need to help them navigate through continuous change?
Agencies should consider a data-insights platform that collects and analyzes data from multiple locations and sources, allowing federal managers to gain deep business insights. Getting there requires a gradual phased approach to reporting and analytics.
Therefore, the data analysis platform should deliver reporting capabilities, as well as all stages of analytics, including:
Reporting: Tells you where you are today
Descriptive analytics: Tells you why you are where you are today
Predictive analytics: Tells you where you are going to be tomorrow
Prescriptive analytics: Tells you what changes your agency needs to make to be somewhere else tomorrow
Agencies must have the infrastructure to get to those points of decision. Too often, traditional data warehouse platforms can be plagued both by high entry and incremental operation costs as well as operational performance, scalability and data security concerns.
Moving away from limited-range tools
An MPaaS can deliver rapid business insights by enabling organizations to move from data silos with limited-range tools to leveraging the latest in automation, AI/ML, and scalable cloud resources. Key benefits of this approach include:
During data preparation, AI can be used to improve data quality, reducing the manual effort required to prepare high-quality data for consumption.
Unlimited amounts of data from disparate systems can be stored in a data lake in open formats while accessible via high-performance query engines to other applications.
By using the latest in explainable AI and big data tools that can easily scan petabytes of structured and unstructured data, data scientists can find outliers in data. Data scientists typically develop an informed theory and then go about exploring data to support or refute that mobile theory, essentially looking for needles in a haystack. They can leverage ML to find the needles in the haystack without even knowing what those needles might look like (that is, without being informed)
Agencies are in various stages of developing a data-driven culture within their organizations. If an agency does not have a platform, managed service providers can install and configure one that has built-in capabilities to store data and is a high-performing secure environment. If an agency already has a data platform, then a managed services provider brings analysts with the knowledge of how to apply data, analytics, AI/ML, and human judgment to achieve business outcomes. Agencies can leverage the economies of scale, best practices and cost efficiencies of managed services.
Accelerated decision-making: Real-world examples
A large government agency has applied managed platforms to streamline the grants selection process. The agency spends hundreds of millions of dollars on grants each year. This agency leveraged both an MPaaS to accelerate its journey to insights and a managed data analytics service, assisted by AI/ML analysis, to rapidly identify the drivers and enablers of both desired and undesired outcomes. As a result, the agency has improved its core performance metrics by optimizing the distribution of money to select high-performing grantees and candidate profiles.
Another organization’s analytical process affecting $1 billion in spending took over four weeks on their traditional data warehouse. The agency dramatically improved its operational processing of data by leveraging an established MPaaS powered by AI/ML, reducing the runtime of the analytical process to 48 hours.
The key to achieving deep understanding of data, discovering actionable insights, and developing course correction plans is to leverage innovative and cost-effective data platforms along with utilizing expertise in data science.
Using data insights, MPaaS can cost-effectively accelerate an agency’s journey towards gaining unfettered access to troves of data. And employing data analytics managed service, assisted by AI/ML, can rapidly accelerate the journey towards gaining actionable insights.
Leveraging a combination of both MPaaS and managed services can free an agency’s resources from the tactical operation and oversight of data management and analysis and free those resources for the strategic navigation and course corrections of the mission’s journey.
Keith Kapp is the chief technology officer of CVP.
HHS digital investigators connect with cloud to manage ever-growing data for legal cases