Prevent Fraud and Waste
Explosive data growth has increased the complexity of government agencies attempting to detect fraud waste in abuse, while also efficiently accomplishing their missions. One federal agency with a large pool of beneficiaries turned to Apache Hadoop and the Hortonworks Data Platform to discover fraudulent claims for benefits. The implementation reduced ETL processing from 9 hours to 1 hour, which allowed them to create new data models around fraud, waste and abuse. After significantly increasing the efficiency of their ETL process, the agency used the surplus processing time and resources to triple the data included in its daily processing. Because Hadoop is a “schema on read” system, rather than the traditional “schema on load” platform, the agency now plans to search additional legacy systems and include more upstream contextual data (such as social media and online content) in its analysis. All of this will make it easier to identify and stop fraud, waste, and abuse.
With the continuing trend of the connected world and requisite big data needs comes big obstacles and even bigger opportunities. City, Local, and State Governments are challenged with establishing and managing an infrastructure built for connected technologies in an ‘Internet of Anything’ environment. These connected devices (sensors, smart meters, medical devices, road telemetry devices, fleet management sensors, emergency response devices, etc) will generate vast amounts of data that need to be processed in real-time to provide valuable insights and actionable intelligence. Additionally, storage and access of this data can provide historical insights and predictive analytics.
With Hortonworks Connected Data Platforms, Public Sector organizations can build a modern Data Analytics platform that is enterprise grade, highly scalable, and multi-tenant. Using Hortonworks Data Flow (HDF), the data from the various sensors and devices can be collected, aggregated, correlated, and processed in real-time and leveraged to perform a desired task. This data is then stored in the Hortonworks Data Platform (HDP) where large volumes of data at petabyte scale can be stored and processed on commodity hardware at much lower cost than traditional systems. Additional nodes can be added with ease to a cluster as the data demand increases.
Single View of a Resource
Whether a Soldier, a Student, or a Military Aircraft, Public Sector customers are overwhelmed with data from various sources and different formats that are often stored in siloed architectures and requiring unique applications and/or complex translations to simply view the data. Correlation of the data in these environments is both complicated and costly. In many instances these systems have no way of communicating.
With Hortonworks Connected Data Platform, Public Sector customers can build an Analytics Data Platform that enables a Single View capability of both Data in Motion and Data at Rest. Real-time data from sensors and other sources (i.e., social media) is collected, logically correlated, and linked while in flight using Hortonworks Data Flow (HDF). Once collected and correlated, it is stored in Hortonworks Data Platform (HDP) where the unmodified data is retained indefinitely and used for future historical analysis and advanced analytics.
Single view of the resource is implemented and enabled through entity resolution. In this process, disparate pieces of data related to the resource are linked using attributes that are unique to respective resource, such as a serial number, tail number, student ID, or social security number.