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  <titleInfo>
    <title>Business intelligence and the cloud : strategic implementation guide</title>
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  <name type="personal">
    <namePart>Gendron, Michael S.</namePart>
    <namePart type="date">1957-</namePart>
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  <genre authority="">Electronic books.</genre>
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    <dateIssued encoding="marc">2014</dateIssued>
    <issuance>monographic</issuance>
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  <abstract>How to measure cloud computing options and benefits to impact business intelligence infrastructure This book is a guide for managers and others involved in using cloud computing to create business value. It starts with a discussion of the media hype around cloud computing and attempt to pull together what industry experts are saying in order to create a unified definition. Once this foundation is created-assisting the reader's understanding of what cloud computing is-the discussion moves to getting business benefits from cloud computing. Lastly, the discussion focuses on examples of cloud computing, public clouds, private clouds, and virtualization.</abstract>
  <tableOfContents>Business Intelligence and the Cloud: Strategic Implementation Guide; Copyright; Contents; Foreword; Preface; Acknowledgments; Part 1: The Foundation; Chapter 1: A History of How We Got to Cloud Computing; The Rise of Cloud Computing; Computing Hardware; Networking and HTML; Bandwidth; Computing Platforms; Cloud Computing; Conclusion; Notes; Chapter 2: Characteristics and Service Models; Introductory Concepts; Layers of Abstraction; Hosted Applications versus Cloud Computing; Corporate LAN-Based versus Cloud-Based Applications; A Cloud Implementation; Defining Cloud Computing.</tableOfContents>
  <tableOfContents>Dimension One: Essential CharacteristicsDimension Two: Service Models; Dimension Three: Deployment Models; Conclusion; Notes; Chapter 3: Deployment Models; Important Considerations; Public and Private Clouds; Examples of Cloud Computing; An IaaS Example: Netflix Moves to Amazon Web Services; A PaaS Example: Sopima Moves to Microsoft Azure; A SaaS Example: Dunkin' Donuts Uses Salesforce; Private Clouds in Context; Puma and Eucalyptus: A Private Cloud Solution; Hybrid Clouds; Zynga: A Hybrid Cloud Example; Community Clouds; Conclusion; Notes; Part 2: Cloud Economics.</tableOfContents>
  <tableOfContents>Chapter 4: Strategic Measurement: TCO, ROI, OPEX/CAPEXTotal Cost of Ownership; How TCO Changes in the Cloud; Build versus Buy; Financial Measurements; Capital Expense (CAPEX) versus Operational Expense (OPEX); Return on Investment (ROI); Conclusion; Notes; Chapter 5: Cloud Adoption: Are Your Organization and Its Stakeholders Ready to Adopt Cloud Computing?; Regulatory Influence; The Effects on Your Organization; The Non-IT Staff; The IT Department; The Effects on External Stakeholders; The Need for Increased Technology; Changes in Payment Models-Changing Costs; The Training of Staff.</tableOfContents>
  <tableOfContents>Requests for Increased InnovationConclusion; Notes; Chapter 6: Service Level Agreements; The Traditional or Typical Telecom SLA QOS; Introducing the Cloud SLA; SLA Types; Cloud Use Cases; SLA by Type of Service and Deployment; Anatomy of a Standardized SLA; Negotiating the Cloud SLA; Step 1: Understand Roles and Responsibilities; Step 2: Evaluate Data Policies and Business Policies; Step 3: Understand Service and Deployment Model Differences; Step 4: Identify Critical Performance Objectives; Step 5: Evaluate Security and Privacy Requirements; Step 6: Identify Service Management Requirements.</tableOfContents>
  <tableOfContents>Step 7: Prepare for Service Failure ManagementStep 8: Understand the Disaster Recovery Plan; Step 9: Develop an Effective Management Process; Step 10: Understand the Exit Process; SLA Expectations; Conclusion; Notes; Part 3: Business Intelligence and the Cloud; Chapter 7: Business Intelligence: The Interaction of Business Intelligence and Cloud Computing; BI Strategy; Objectives for a BI Project; The Analytics Cycle; Data Collection; Data Analysis; Data Distribution; Conclusion; Notes; Chapter 8: Big Data's Effects on BI Efforts in the Cloud; Defining Big Data; High Volume; High Velocity.</tableOfContents>
  <tableOfContents>High Variety.</tableOfContents>
  <note type="statement of responsibility">Michael S. Gendron.</note>
  <note>Includes index.</note>
  <note>Includes bibliographical references and index.</note>
  <subject authority="lcsh">
    <topic>Information technology</topic>
    <topic>Management</topic>
  </subject>
  <subject authority="lcsh">
    <topic>Cloud computing</topic>
  </subject>
  <subject authority="lcsh">
    <topic>Business intelligence</topic>
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    <topic>Business</topic>
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  <subject>
    <topic>Information technology</topic>
    <topic>Management</topic>
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  <subject authority="bisacsh">
    <topic>BUSINESS &amp; ECONOMICS</topic>
    <topic>Industrial Management</topic>
  </subject>
  <subject authority="bisacsh">
    <topic>BUSINESS &amp; ECONOMICS</topic>
    <topic>Management</topic>
  </subject>
  <subject authority="bisacsh">
    <topic>BUSINESS &amp; ECONOMICS</topic>
    <topic>Management Science</topic>
  </subject>
  <subject authority="bisacsh">
    <topic>BUSINESS &amp; ECONOMICS</topic>
    <topic>Organizational Behavior</topic>
  </subject>
  <subject authority="fast">
    <topic>Business intelligence</topic>
  </subject>
  <subject authority="fast">
    <topic>Cloud computing</topic>
  </subject>
  <subject authority="fast">
    <topic>Information technology</topic>
    <topic>Management</topic>
  </subject>
  <classification authority="lcc">HD30.2</classification>
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      <namePart>Gendron, Michael S., 1957-</namePart>
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    <originInfo>
      <publisher>Hoboken, New Jersey : John Wiley &amp; Sons, Inc., [2014]</publisher>
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