Resource Library

Cloudera offers a variety of materials on big data consolidation, storage and processing. The library includes high-level overviews as well as detailed information on Apache Hadoop and the surrounding ecosystem.

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    Opower Uses Big Data to Help Consumers Save $320 Million in Utility Bills
    • Tuesday, Nov 19 2013
    • File Type: .PDF
    • Category: Document, Case Studies
    OPower uses Big Data to measure utility usage efficencies and deliver the results to users. This allows users the ability to identify their own habits and inefficiencies and adjust their behavior towards further consumptive efficacy.
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    DataSift: Allowing Enterprises to Benefit from Social Data Using Hadoop
    • Wednesday, Nov 07 2012
    • File Type: .PDF
    • Category: Case Studies, Document
    DataSift is a real-time data processing platform that processes, aggregates, and filters data from billions of public social conversations in both real time and historically.
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    Intel and Cloudera Help Design a Content Recommendation Engine for Chinese Content
    • Thursday, Aug 06 2015
    • File Type: .PDF
    • Category: Predictive modeling, Case Studies, Document
    Using Intel algorithms customized for the written Chinese language, a regional media publisher increases readership and advertisement revenues.
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    Intel and Cloudera Help Improve a Company’s Text-Based Searches Resulting in Increased Revenue
    • Thursday, Aug 06 2015
    • File Type: .PDF
    • Category: Document, Case Studies
    Intel and Cloudera redesign a company’s search engine, providing text-based recommendations, improved search results, faster performance, and more revenues.
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    Intel and Cloudera Help a Company Use Predictive Analytics to Foresee Future Purchasing Behaviors
    • Friday, Aug 14 2015
    • File Type: .PDF
    • Category: Case Studies, Document, Predictive modeling, Retail, eCommerce & Consumer Products, Personalization & recommendations
    Intel and Cloudera implement a solution to ingest multiple data sources, using the information to create variables to predict buying trends among customers.
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    Intel and Cloudera Help a Large Hospital Group Allocate Resources by Predicting Patient Length-of-Stay
    • Thursday, Aug 06 2015
    • File Type: .PDF
    • Category: Case Studies, Document, Healthcare & Life Sciences, Predictive modeling
    With a more accurate length-of-stay prediction model, hospitals can allocate personnel and resources more efficiently, thus reducing operational costs.
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    Patterns and Predictions Uses Big Data to Predict Veteran Suicide Risk
    • Tuesday, Aug 27 2013
    • Category: Cloudera Enterprise, Case Studies, Document
    Patterns and Predictions uses Hadoop to power The Durkheim Project – a Big Data analytics network that assesses mental health risk, in real time and at scale, through a machine learning framework that runs on CDH, leveraging Cloudera Search and Cloudera Impala.
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    CSC Expedites Big Data Application Development for Government
    • Monday, Sep 15 2014
    • File Type: .PDF
    • Category: Document, Case Studies
    By deploying Cloudera within its EzBake application engine, CSC has built a scalable framework that reduces the barrier to entry for federal developers to migrate their Big Data applications to a cloud-based enterprise data hub environment, with standardized security right out of the box.
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    Nokia: Using Big Data to Bridge the Virtual & Physical Worlds
    • Monday, Apr 09 2012
    • File Type: .PDF
    • Category: Case Studies, About Cloudera, Document, Data warehousing offload, Data processing ETL offload, Data hub
    Effective collection and use of data has become central to Nokia’s ability to understand and improve users’ experiences with their phones and other location products.
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    Pentaho edo Success Story
    • Wednesday, Feb 04 2015
    • File Type: .PDF
    • Category: Case Studies, Document
    edo’s data scientists have reduced query times to only 30 minutes via Hive and have seen sub-second query times when utilizing Impala. As edo’s data scientists migrate to Impala, they can ask more questions of their data, bringing more value to their customers.