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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.
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.
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.
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.
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.
アリゾナ州立大学（ASU）は全米最大の在籍者数を誇る公立大学です。83,000 人以上の学生と 3,300 人の教職員が在籍しています。2014 年に評議委員会によって承認された ASU チャーターは、ASU 学長のマイケル・M・クロウが作成した「新しいアメリカの大学」モデルに基づいています。その中で ASU は次のように定義付けられています：「包括的...
The United Network for Organ Sharing (UNOS) is the private, non-profit organization managing the United States organ transplant system. UNOS brings together hundreds of hospitals, transplant centers, organ procurement professionals, and thousands of volunteers. The mission of UNOS is to advance organ availability and transplantation by uniting and supporting communities for the benefit of patients…
セントルイスの Metro Transit（MTL）は、セントルイス首都圏地域の公共交通システムを運営しています。組織のミッションは「財政的に責任ある方法で、安全で信頼性と利便性の高い顧客中心のサービスを提供することで、地域の輸送ニーズを満たす」です。安全で信頼性の高い公共交通機関を提供することで乗客の安全を確保するという挑戦に打ち勝ち...
UC Irvine Health は Hadoop と Hortonworks Data Platform を活用して、病院での医療活動や医学部の科学的研究を向上させています。このチームは医療行為を数値化することで、再入院の減少、新たな研究プロジェクトの高速化、分刻みでの患者のバイタルサイン監視を実現しています。1 つの Hadoop プラットフォームで 2 つの異なる...
2014 年 12 月 10 日
2015 年 10 月 1 日