As reliance on data takes center stage in critical decision-making processes, the creation of an end-to-end data strategy—focusing on mission impact with clearly defined goals—becomes imperative. Tactically planning and strategically executing the collection, storage, and analysis of data offers myriad benefits to federal agencies, including deeper insights, accelerated business effectiveness, and more efficient operations. Secondary effects include more secure data, enhanced data sharing, and more accurate compliance monitoring, all while achieving improved cost efficiencies.
Organizations across the federal space recognize the power of data, but the challenge remains to implement a systematic roadmap to achieve data-driven success. How can federal agencies ensure that their efforts to gain insight from data produce much-needed mission enablement?
Think Beyond Data Warehouses
When organizations understand the sheer volume of available data—from their own operations, that of their partners, and open sources—the first inclination is to collect and hoard. But copying and storing data in one place ignores modern best practices. The magnitude of managing and curating so much data, while tracking the duplication of efforts created for reporting and compliance purposes, will quickly overwhelm even the most robust budgets and advanced storage facilities. This can lead to unsustainable operations and maintenance (O&M) outcomes and high security risks.
Rather than build a data warehouse, agencies should first focus on understanding the tools, systems, and methods surrounding data collection, management, and analysis. Once equipped with an understanding of their unique data landscape, they can select the appropriate solution—hybrid data lakes with external stakeholders, service-focused data streams, etc.—to synthesize, manage, and analyze data while honoring data privacy and ownership concerns.
Build Functionality Using Microservices
Legacy architecture and builds often rely on large, monolithic databases feeding multiple systems, with business processes crossing several boundaries. Maintaining these systems while responding to a new mission scope—aggregating data for analysis and interpretation—not only results in costly O&M, but also lacks efficiency and scalability.
By starting with a holistic approach that focuses on mission first, agencies can pivot from stove-piped architectures—centered around applications and business processes—into agile, dynamic mission “apps” composed of multiple microservices. These microservices enhance organizational strategy by simplifying and standardizing system architecture, making it easier to solve the enterprise challenges that face large, complex systems. Because microservices encapsulate all the data within a given capability, they provide data scientists with a self-contained data source from which to perform the analysis necessary for critical decision-making.
Through the implementation of microservices architecture, organizations not only solve their most vexing data management challenges, but can also take advantage of the latest automation technologies to improve operations. By employing microservices with robust quality assurance (QA) processes and controls, agencies can increase confidence in data quality, data sharing, and the successful decoupling of legacy systems and data. This serves to minimizes technical debt and improves the ability to transition effectively from risk-based to data-driven decision-making processes, increasing trust in data and shortening the decision cycle time.
Gain Meaningful Insight through Mission Connection
In the field of data science, “big data” has given way to machine learning (ML) and artificial intelligence (AI). But realizing full value from these automated technologies is not an easy achievement. Agencies must follow a multilayered approach, drawing on both tools and experienced resources. Data scientists, automation engineers, and developers focused on customer experience must work closely with owners and stakeholders to implement a comprehensive, end-to-end data strategy that focuses first on the mission at hand. Relying on new tools without the necessary expertise only results in increased costs.
A complete data strategy enables federal agencies to achieve mission goals such as efficiency, quality, customer service, and scalability. By leveraging these recommendations, agencies can design and deploy a successful roadmap towards modernizing and automating their businesses.
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