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공공 기관 및 정부를 위한
빅 데이터 비즈니스 인텔리전스 및 분석

클라우드 Hortonworks는 리더입니다. Forrester Wave를 읽어보세요.

보고서 다운로드

애리조나 주립 대학에서는 HDP® 를 사용하여 갇혀 있던 통찰력을 모두 활용합니다.

애리조나 주립 대학(ASU)은 미국에서 가장 큰 대학교로, 2016년에는 U.S. News & World Report에 의해 "미국에서 가장 혁신적인 학교"로 선정되었습니다. ASU의 복합 적응형 시스템 이니셔티브(Complex Adaptive Systems Initiative: CASI)에서는 수백 명의 개인에 대한 수 페타바이트의 유전 데이터가 포함된 게놈 Data Lake를 구축하여 개별적인 게놈의 변형이 각각 암 유전자의 발현에 영향을 미칠 수 있는 방법에 대한 연구를 지원합니다.

데이터의 힘으로 혜택을 받는 공공 부문

공공 기관들은 여러 다양한 소스에서 제공되는 여러 가지 형식의 데이터로부터 실질적인 인텔리전스를 추출하는 데 어려움을 겪고 있습니다. 설상가상으로 리소스와 예산은 제한적입니다. Hortonworks 연결 데이터 플랫폼을 활용하는 당사의 고객은 제공되는 모든 데이터를 통해 저렴한 가격으로 경쟁적 우위를 점할 수 있습니다.

이용 사례

머신 및 센서 데이터를 사용한 공공 인프라의 능동적 유지관리

Metro Transit of St. Louis (MTL) operates the public transportation system for the St. Louis metropolitan region. Hortonworks Data Platform helps MTL meet their mission by storing and analyzing IoT data from the city’s Smart Buses, which helped the agency cut average cost per mile driven by its buses from $0.92 to $0.43. It achieved that cost reduction while simultaneously doubling the annual miles driven per bus. Hortonworks delivered the MTL solution in partnership with LHP Telematics, an industry leader in creating custom telematics solutions for connected vehicles in the heavy equipment OEM marketplace, transportation, service, and construction fleets. The combined solution is making MTL bus service more reliable–improving the Mean Time Between Failures (MTBF) for metro buses by a factor of five, from four thousand to twenty-one thousand miles.

Similarly, a Department of Defense customer has turned to Hortonworks Connected Data Platforms to enable analytics and preventative maintenance on their fleet of aircraft. With HDP and HDF, the customer is able obtain predictive analytics and actionable intelligence on their platforms. In addition to reduced Total Cost of Ownership, realized results have included tangible improvements in lifecycle management, operational readiness, pilot safety, and supply management.


Enterprise Data Warehouse (EDW) Optimization

The Enterprise Data Warehouse has become a standard component of enterprise data architectures. However, the complexity and volume of data has posed some interesting challenges to the efficiency of the existing EDW solution. Realizing the transformative potential of Big Data depends on an organization’s ability to manage complexity, while leveraging various and disparate new data sources such as social, web, IoT and more. The integration of these new data sources into the existing EDW system is often costly and incredibly complex.

Hortonworks Enterprise Data Warehouse Optimization Solution is the industry’s only turnkey Hadoop-powered Business Intelligence (BI) solution. The EDW Optimization Solutions is powered by Hortonworks Data Platform (HDP®) and technology from partners Syncsort and AtScale. With the EDW Optimization Solution, Public Sector users can extend the value of existing EDW investments and overcome the challenges, risks and costs of introducing new solutions into legacy infrastructure.

The solution can be implemented rapidly, makes fast BI on Hadoop a reality and reduces cost by moving non-critical workloads off the EDW and leveraging the cost-effective archiving in Hadoop.


University Health Care

Difficult challenges and choices face today’s healthcare industry. Researchers, clinicians and administrators have to make important decisions – often without sufficient data. Hortonworks Connected Data Platforms (powered by Apache Hadoop and Apache NiFi) make healthcare data available and actionable.

By partnering with Hortonworks, researchers can access genomic data for new cancer treatments, physicians can monitor patient vitals and sensor data in real time, hospitals can reduce re-admittance rates, and universities can store medical research data forever.


부정 행위 및 낭비 방지

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.

Smart Cities

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.

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