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  <titleInfo>
    <title>Modern Data Analytics in Excel</title>
    <subTitle>Using Power Query, Power Pivot, and more for Enhanced Data Analytics</subTitle>
  </titleInfo>
  <name type="personal">
    <namePart>Mount, George</namePart>
    <namePart type="termsOfAddress">(Writer on data analytics)</namePart>
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  <genre authority="lcgft">Instructional and educational works.</genre>
  <genre authority="rvmgf">Matériel d'éducation et de formation.</genre>
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    </place>
    <dateIssued encoding="marc">2024</dateIssued>
    <copyrightDate encoding="marc">2024</copyrightDate>
    <edition>First edition.</edition>
    <issuance>monographic</issuance>
  </originInfo>
  <language>
    <languageTerm authority="iso639-2b" type="code">eng</languageTerm>
  </language>
  <physicalDescription>
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    <extent>xvi, 224 pages : illustrations ; 24 cm</extent>
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  <abstract>If you haven't modernized your data cleaning and reporting processes in Microsoft Excel, you're missing out on big productivity gains. And if you're looking to conduct rigorous data analysis, more can be done in Excel than you think. This practical book serves as an introduction to the modern Excel suite of features along with other powerful tools for analytics. George Mount of Stringfest Analytics shows business analysts, data analysts, and business intelligence specialists how to make bigger gains right from your spreadsheets by using Excel's latest features. You'll learn how to build repeatable data cleaning workflows with Power Query, and design relational data models straight from your workbook with Power Pivot. You'll also explore other exciting new features for analytics, such as dynamic array functions, AI-powered insights, and Python integration. Learn how to build reports and analyses that were previously difficult or impossible to do in Excel. This book shows you how to: Build repeatable data cleaning processes for Excel with Power Query Create relational data models and analysis measures with Power Pivot Pull data quickly with dynamic arrays Use AI to uncover patterns and trends from inside Excel Integrate Python functionality with Excel for automated analysis and reporting.</abstract>
  <note type="statement of responsibility">George Mount.</note>
  <note>Includes index.</note>
  <note>Includes exercise.</note>
  <subject authority="lcsh">
    <titleInfo>
      <title>Microsoft Excel (Computer file)</title>
    </titleInfo>
  </subject>
  <subject authority="lcsh">
    <topic>Electronic spreadsheets</topic>
    <topic>Computer programs</topic>
  </subject>
  <subject authority="lcsh">
    <topic>Business</topic>
    <topic>Computer programs</topic>
  </subject>
  <subject authority="rvm">
    <topic>Tableurs</topic>
    <topic>Logiciels</topic>
  </subject>
  <classification authority="lcc">HF5548.4.M523 M68 2024</classification>
  <classification authority="ddc" edition="23">005.54</classification>
  <identifier type="isbn">9781098148829</identifier>
  <identifier type="isbn">1098148827</identifier>
  <identifier type="lccn">2024391723</identifier>
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    <recordIdentifier source="MYCC">807</recordIdentifier>
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