rdf-syntax-grammar
mods:
  schema location: http://www.loc.gov/mods/v3 http://www.loc.gov/standards/mods/v3/mods-3-2.xsd
  title info:
    title: Pro SQL Server 2012 BI Solutions
  name:
    name part: Root, Randal.
    role:
      role term: creator
    role:
      role term: author.
  name:
    name part: Mason, Caryn.
    role:
      role term: author.
  name:
    name part: SpringerLink (Online service)
  type of resource: text
  origin info:
    place:
      place term: xxu
    date issued: 2012
    issuance: monographic
  language:
    language term: eng
  physical description:
    form: electronic
    form: electronic resource
    reformatting quality: access
    form: remote
    extent: XXVII, 836 p. online resource.
  abstract: Business intelligence projects do not need to cost multi-millions of dollars or take months or even years to complete! Using rapid application development (RAD) techniques along with Microsoft SQL Server 2012, this book guides database administrators, SQL programmers, and report specialists in creating practical, cost-effective business intelligence solutions for their companies and departments. Pro SQL Server 2012 BI Solutions provides practical examples of cost-effective business intelligence projects. Readers will be guided through several complete projects that build a foundation for real-world solutions. Even with limited experience using Microsoft's SQL Server, Integration Server, Analysis Server, and Reporting Server, you can leverage your existing knowledge of SQL programming and database design to provide users with the business intelligence reports they need. Provides recipes for multiple business intelligence scenarios Progresses from simple to advanced projects using several examples Shows Microsoft SQL Server technology used to complete real-world business intelligence projects.
  note: by Randal Root, Caryn Mason.
  subject:
    topic: Computer science
  subject:
    topic: Data mining
  subject:
    topic: Computer Science
  subject:
    topic: Computer Science, general
  subject:
    topic: Data Mining and Knowledge Discovery
  classification: QA75.5-76.95
  classification: 004
  related item:
    title info:
      title: Springer eBooks
  identifier: 9781430234890
  identifier: http://dx.doi.org/10.1007/978-1-4302-3489-0
  record info:
    record creation date: 121026
    record change date: 20150520200038.0
    record identifier: 978-1-4302-3489-0