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  <titleInfo>
    <title>Learning Microsoft Power BI</title>
    <subTitle>Transforming Data into Insights</subTitle>
  </titleInfo>
  <name type="personal">
    <namePart>Arnold, Jeremey</namePart>
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    <dateIssued encoding="marc">2022</dateIssued>
    <edition>First edition.</edition>
    <issuance>monographic</issuance>
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  <language>
    <languageTerm authority="iso639-2b" type="code">eng</languageTerm>
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  <physicalDescription>
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    <extent>xv, 290 pages : illustrations, maps ; 24 cm</extent>
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  <abstract>"Microsoft Power BI is a data analytics and visualization tool powerful enough for the most demanding data scientists, but accessible enough for everyday use for anyone who needs to get more from data. The market has many books designed to train and equip professional data analysts to use Power BI, but few of them make this tool accessible to anyone who wants to get up to speed on their own. This streamlined intro to Power BI covers all the foundational aspects and features you need to go from zero to hero with data and visualizations. Whether you work with large, complex datasets or work in Microsoft Excel, author Jeremey Arnold shows you how to teach yourself Power BI and use it confidently as a regular data analysis and reporting tool."--</abstract>
  <tableOfContents>Intro to Power BI -- The report and data views -- Importing and modeling our data -- Let's make some pictures (Visualizing data 101) -- Aggregations, Measures and DAX -- Putting the puzzle pieces together: From raw data to report -- Advanced reporting topics in Power BI -- Introduction to the Power BI service -- Licensing and deployment tips -- Third-Party Tools</tableOfContents>
  <note type="statement of responsibility">Jeremey Arnold.</note>
  <note>Includes index.</note>
  <subject authority="lcsh">
    <titleInfo>
      <title>Microsoft Power BI (Computer file)</title>
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  </subject>
  <subject authority="fast">
    <titleInfo>
      <title>Microsoft Power BI (Computer file)</title>
    </titleInfo>
  </subject>
  <subject authority="lcsh">
    <topic>Quantitative research</topic>
    <topic>Data processing</topic>
  </subject>
  <subject authority="lcsh">
    <topic>Information visualization</topic>
    <topic>Computer programs</topic>
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  <subject authority="lcsh">
    <topic>Database design</topic>
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    <topic>Information visualization</topic>
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  <classification authority="lcc">QA76.9.Q36 A75 2022</classification>
  <classification authority="ddc" edition="23">005.72</classification>
  <identifier type="isbn">9781098112844</identifier>
  <identifier type="isbn">1098112849</identifier>
  <identifier type="lccn">2023277325</identifier>
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