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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    Multitenancy and the Enterprise Data Hub
    • Thursday, Mar 20 2014
    • File Type: .PDF
    • Category: Cloudera Enterprise, Document, White Papers
    Best practices and architectures for multiple services and user communities in Apache Hadoop
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    Evaluating Hardware Platforms for Cloudera
    • Thursday, Mar 20 2014
    • File Type: .PDF
    • Category: Document, White Papers
    An enterprise data hub (EDH) brings to enterprise IT teams a range of capability and efficiency, and these qualities also extend to deployment and operations, from on-premise to public cloud. Cloudera strives to make its software available to enterprises in as many form factors as possible from as many technology partners as possible.
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    Hadoop and HDFS
    • File Type: .PDF
    • Category: Document, White Papers
    Enterprises are rapidly discovering the power of Apache Hadoop and big data to drive more powerful, data-driven insights and better position their organizations in an increasingly dynamic and competitive economy. Hadoop’s innovation in scalability, cost efficiency, and flexibility affords enterprises an unprecedented ability to handle greater volume, greater velocity, and greater variety of data than traditional data management technologies. For these information-driven enterprises, this next step in the evolution of data management is an enterprise data hub.
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    Hadoop - Extending Your Data Warehouse
    • Tuesday, Apr 23 2013
    • File Type: .PDF
    • Category: About Hadoop, White Papers, Document, Data hub, Data processing ETL offload, Data warehousing offload
    Register to receive this recently published whitepaper, Hadoop: Extending Your Data Warehouse by Tony Baer, Principal Analyst, Ovum IT Enterprise Solutions, to learn how to get started on bringing Hadoop into your EDW and BI architectures.
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    TDWI Best Practices Report:
    Integrating Hadoop into Business Intelligence and Data Warehousing
    • Monday, Apr 01 2013
    • File Type: .PDF
    • Category: White Papers, Analyst Reports, apache hadoop, Data processing ETL offload, Data warehousing offload, Analytics & Business Intelligence
    Hadoop promises to assist with the toughest challenges in BI today, including big data, advanced analytics, and multi-structured data. Download this TDWI Best Practices Report to learn how to integrate Hadoop into your business intelligence, analytics, data integration, and data warehousing technology stacks.
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    Ask Bigger Questions: A Round Table Discussion
    • Sunday, Oct 21 2012
    • File Type: .PDF
    • Category: Document, White Papers
    In this exclusive conversation, the technical leaders of Cloudera discuss the definition, origins, and future of Big Data and Apache Hadoop — and their value for business and humankind.
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    CDH & Enterprise Security
    • Monday, Sep 17 2012
    • File Type: .PDF
    • Category: White Papers, About Cloudera, CDH, Document
    Understand the security models available in CDH and the related components required to deploy and maintain a secure CDH environment.
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    Why Are Financial Services Firms Adopting Cloudera's Big Data Solutions?
    • Thursday, Sep 06 2012
    • File Type: .PDF
    • Category: White Papers, Case Studies, Document
    Cloudera helps financial services companies implement and manage Apache Hadoop so they can derive competitive advantage from big data.
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    Using Cloudera to Improve Data Processing
    • Thursday, Sep 06 2012
    • File Type: .PDF
    • Category: White Papers, About Cloudera, Document
    Cloudera simplifies data processing, which is critical to supporting everyday operations such as report generation, measuring internal metrics day-to-day, and reporting quarterly financial results.
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    What is Data Science?
    • Wednesday, Nov 10 2010
    • File Type: .PDF
    • Category: White Papers, Document, Resource Type
    Understand where data comes from, working with data at scale, making data tell a story (analysis), and data scientists.