The Case for Big Data, Analytics and Data Science in Government
U.S. Public Sector government agencies are increasingly faced with new challenges to provide new citizen services, decrease time to decision and achieve faster mission success. To address these needs and new requirements, many government agencies have begun the journey of digital transformation with new focus on data as an asset.
Government’s experience with big data and analytics is just beginning. The most commonly used definition of big data describes it as high-volume, high-velocity and high-variety information that requires new forms of processing to enable enhanced decision-making, insight discovery and process optimization. These factors are driving agencies to rethink traditional data storage strategies and create intelligent, ‘data lakes’ to effectively manage ingest and use of dynamic and emerging types, sizes and volumes of data.
Big data analytics can involve vast amounts of structured and unstructured data, which helps government leaders use sophisticated data science techniques and machine learning algorithms to drive decision-making. These algorithms in conjunction with purpose-built advanced analytics can predict behavior (predictive analytics); analyze program integrity to identify problems, such as fraud and abuse; or evaluate policy changes before they are implemented. When combined, big data, analytics and data science represent, disruptive, modern and strategic capabilities for discovering new patterns and correlations in data to create a new outcomes. Ultimately, it’s about leveraging analytics to make data actionable and to create new outcomes.
DLT is taking a leadership position to guide U.S. Public Sector government agencies with a vision of how to effectively incorporate analytics and data management technologies and capabilities to achieve improved data insight and decision-making. Aligned with today’s IT stack methodologies, our approach to address big data analytics and the resulting data management challenges is through an ‘analytics stack’ strategy leveraging ‘best-of-breed’, big data infrastructure, advanced analytics and data science technologies, products and ecosystem solutions.
The DLT AnalyticsStack is a four-layer, technology and solution stack strategy focused on all aspects of big data, advanced analytics and management ranging from foundational aspects like Big Data Processing to Data Lake Management, Master Data Management and Purpose-Built Analytics. Providing improved data insight and supporting a culture of end-user driven analytics, each layer consists of complimentary capabilities to support the needs of agency Executives, Analysts and Data Scientists.
DLT AnalyticsStack V1.0 supports key capabilities needed to create, manage and leverage big data inside your agency.
- Big Data Processing Layer - As a foundational element, this layer is based on big data batch and streaming database and processing technologies like Apache Open Source Hadoop and Spark and transaction-oriented, NoSQL databases like Apache Cassandra and others.
- Data Lake Management Layer – To effectively manage the ingest and use of various types, sizes and volume of data, the Data Lake Management capability creates and manages a metadata catalog for all data in the batch and streaming data clusters deployed in the big data processing layer.
- Master Data Management Layer – To support data ingest wrangling, preparation and integration while providing data governance, compliance, security and protection, the Master Data Management Layer ensures data is ready and available for effective analysis.
- Analytics Layer - Data insight is key to the success of any analytics strategy. The Analytics Layer provides a set of purpose-built analytics and data science capabilities that span everything from self-service, BI to advanced machine learning, deep learning and artificial intelligence.
Data Ingest Support
The DLT AnalyticsStack V1.0 supports a wide-range of data assets and sources for ingest.
- Geo-location Data
- Unstructured Data (images, videos,etc)
- Machine/Sensor/ IoT Data
- Social Media Data
- Server Logs
- JSON/Excel/Text Files
Government Use Cases
The DLT AnalyticsStack V1.0 is highly relevant in addressing the dynamic and emerging, data-driven mission needs of government agencies. An abbreviated list of potential mission use-cases include:
- Citizen and Employee Engagement
- Fraud, Waste and Abuse Detection/Prediction
- Supply Chain Management
- Transparency/Open Data
- Cyber Threat Management
- Healthcare/Hospital Optimization
- Logistics/Asset Management/IoT
- Financial/Budget Accountability
- Workforce Management
- Blue Force Tracking
- Predictive Policing
- Public Safety & Services