eBook
Προβολή σε EDS

SQL for Data Analytics : Analyze Data Effectively, Uncover Insights and Master Advanced SQL for Real-world Applications

Λεπτομέρειες βιβλιογραφικής εγγραφής
Τίτλος: SQL for Data Analytics : Analyze Data Effectively, Uncover Insights and Master Advanced SQL for Real-world Applications
Περιγραφή: Level up from basic SQL to advanced, analytics-grade data analysis and use real PostgreSQL datasets, modern features, and practical business scenarios to turn raw data into clear, actionable insights. Free with your book: DRM-free PDF version + access to Packt's next-gen Reader•Key FeaturesSolve real business problems with advanced SQL techniquesWork with time-series, geospatial, and text data using PostgreSQLBuild job-ready data analysis skills with hands-on SQL projectsPurchase of the print or Kindle book includes a free PDF eBookBook DescriptionSQL remains one of the most essential tools for modern data analysis and mastering it can set you apart in a competitive data landscape. This book helps you go beyond basic query writing to develop a deep, practical understanding of how SQL powers real-world decision-making. SQL for Data Analytics, Fourth Edition, is for anyone who wants to go beyond basic SQL syntax and confidently analyze real-world data. Whether you're trying to make sense of production data for the first time or upgrading your analytics toolkit, this book gives you the skills to turn data into actionable outcomes. You'll start by creating and managing structured databases before advancing to data retrieval, transformation, and summarization. From there, you'll take on more complex tasks such as window functions, statistical operations, and analyzing geospatial, time-series, and text data. With hands-on exercises, case studies, and detailed guidance throughout, this book prepares you to apply SQL in everyday business contexts, whether you're cleaning data, building dashboards, or presenting findings to stakeholders. By the end, you'll have a powerful SQL toolkit that translates directly to the work analysts do every day. •Email sign-up and proof of purchase requiredWhat you will learnWrite SQL Queries to explore and analyze structured data.Use JOINs, subqueries, views, and CTEs to build analytics-ready datasetsApply window functions to identify trends, patterns, and cohort behaviorPerform statistical analysis and hypothesis testing directly in SQLAnalyze JSON, arrays, text, geospatial, and time-series dataImprove SQL performance with indexing strategies and query plan optimizationLoad data with Python and automate analytics workflowsComplete a full case study simulating a real-world data analysis projectWho this book is forThis book is for aspiring and early-career data analysts, data engineers, backend developers, business analysts, and students who want to apply SQL to real-world data analytics. You should have basic SQL familiarity and college-level math knowledge, along with the desire to advance toward analytics-grade SQL, data transformation, pattern discovery, and business insight generation.
Συγγραφείς: Jun Shan, Haibin Li, Matt Goldwasser, Upom Malik, Benjamin Johnston
Resource Type: eBook.
Θέματα: SQL (Computer program language), Data mining
Categories: COMPUTERS / Languages / SQL, COMPUTERS / Data Science / Data Analytics, COMPUTERS / Data Science / Data Warehousing
Βάση Δεδομένων: eBook Index
FullText Text:
  Availability: 0
Header DbId: edsebk
DbLabel: eBook Index
An: 4357280
RelevancyScore: 981
AccessLevel: 6
PubType: eBook
PubTypeId: ebook
PreciseRelevancyScore: 981.043701171875
IllustrationInfo
Items – Name: Title
  Label: Title
  Group: Ti
  Data: SQL for Data Analytics : Analyze Data Effectively, Uncover Insights and Master Advanced SQL for Real-world Applications
– Name: Abstract
  Label: Description
  Group: Ab
  Data: Level up from basic SQL to advanced, analytics-grade data analysis and use real PostgreSQL datasets, modern features, and practical business scenarios to turn raw data into clear, actionable insights. Free with your book: DRM-free PDF version + access to Packt's next-gen Reader•Key FeaturesSolve real business problems with advanced SQL techniquesWork with time-series, geospatial, and text data using PostgreSQLBuild job-ready data analysis skills with hands-on SQL projectsPurchase of the print or Kindle book includes a free PDF eBookBook DescriptionSQL remains one of the most essential tools for modern data analysis and mastering it can set you apart in a competitive data landscape. This book helps you go beyond basic query writing to develop a deep, practical understanding of how SQL powers real-world decision-making. SQL for Data Analytics, Fourth Edition, is for anyone who wants to go beyond basic SQL syntax and confidently analyze real-world data. Whether you're trying to make sense of production data for the first time or upgrading your analytics toolkit, this book gives you the skills to turn data into actionable outcomes. You'll start by creating and managing structured databases before advancing to data retrieval, transformation, and summarization. From there, you'll take on more complex tasks such as window functions, statistical operations, and analyzing geospatial, time-series, and text data. With hands-on exercises, case studies, and detailed guidance throughout, this book prepares you to apply SQL in everyday business contexts, whether you're cleaning data, building dashboards, or presenting findings to stakeholders. By the end, you'll have a powerful SQL toolkit that translates directly to the work analysts do every day. •Email sign-up and proof of purchase requiredWhat you will learnWrite SQL Queries to explore and analyze structured data.Use JOINs, subqueries, views, and CTEs to build analytics-ready datasetsApply window functions to identify trends, patterns, and cohort behaviorPerform statistical analysis and hypothesis testing directly in SQLAnalyze JSON, arrays, text, geospatial, and time-series dataImprove SQL performance with indexing strategies and query plan optimizationLoad data with Python and automate analytics workflowsComplete a full case study simulating a real-world data analysis projectWho this book is forThis book is for aspiring and early-career data analysts, data engineers, backend developers, business analysts, and students who want to apply SQL to real-world data analytics. You should have basic SQL familiarity and college-level math knowledge, along with the desire to advance toward analytics-grade SQL, data transformation, pattern discovery, and business insight generation.
– Name: Author
  Label: Authors
  Group: Au
  Data: <searchLink fieldCode="AR" term="%22Jun+Shan%22">Jun Shan</searchLink><br /><searchLink fieldCode="AR" term="%22Haibin+Li%22">Haibin Li</searchLink><br /><searchLink fieldCode="AR" term="%22Matt+Goldwasser%22">Matt Goldwasser</searchLink><br /><searchLink fieldCode="AR" term="%22Upom+Malik%22">Upom Malik</searchLink><br /><searchLink fieldCode="AR" term="%22Benjamin+Johnston%22">Benjamin Johnston</searchLink>
– Name: TypePub
  Label: Resource Type
  Group: TypPub
  Data: eBook.
– Name: Subject
  Label: Subjects
  Group: Su
  Data: <searchLink fieldCode="DE" term="%22SQL+%28Computer+program+language%29%22">SQL (Computer program language)</searchLink><br /><searchLink fieldCode="DE" term="%22Data+mining%22">Data mining</searchLink>
– Name: SubjectBISAC
  Label: Categories
  Group: Su
  Data: <searchLink fieldCode="ZK" term="%22COMPUTERS+%2F+Languages+%2F+SQL%22">COMPUTERS / Languages / SQL</searchLink><br /><searchLink fieldCode="ZK" term="%22COMPUTERS+%2F+Data+Science+%2F+Data+Analytics%22">COMPUTERS / Data Science / Data Analytics</searchLink><br /><searchLink fieldCode="ZK" term="%22COMPUTERS+%2F+Data+Science+%2F+Data+Warehousing%22">COMPUTERS / Data Science / Data Warehousing</searchLink>
PLink https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edsebk&AN=4357280
RecordInfo BibRecord:
  BibEntity:
    Classifications:
      – Code: 005.7585
        Scheme: ddc
        Type: prePub
    Languages:
      – Code: eng
        Text: English
    Subjects:
      – SubjectFull: SQL (Computer program language)
        Type: general
      – SubjectFull: Data mining
        Type: general
    Titles:
      – TitleFull: SQL for Data Analytics : Analyze Data Effectively, Uncover Insights and Master Advanced SQL for Real-world Applications
        Type: main
  BibRelationships:
    HasContributorRelationships:
      – PersonEntity:
          Name:
            NameFull: Jun Shan
      – PersonEntity:
          Name:
            NameFull: Haibin Li
      – PersonEntity:
          Name:
            NameFull: Matt Goldwasser
      – PersonEntity:
          Name:
            NameFull: Upom Malik
      – PersonEntity:
          Name:
            NameFull: Benjamin Johnston
      – PersonEntity:
          Name:
            NameFull: Jun Shan
      – PersonEntity:
          Name:
            NameFull: Haibin Li
      – PersonEntity:
          Name:
            NameFull: Matt Goldwasser
      – PersonEntity:
          Name:
            NameFull: Upom Malik
      – PersonEntity:
          Name:
            NameFull: Benjamin Johnston
    IsPartOfRelationships:
      – BibEntity:
          Dates:
            – D: 01
              M: 01
              Type: published
              Y: 2025
            – D: 03
              M: 12
              Type: profile
              Y: 2025
          Identifiers:
            – Type: isbn-print
              Value: 9781836646259
            – Type: isbn-electronic
              Value: 9781836646242
          Titles:
            – TitleFull: SQL for Data Analytics : Analyze Data Effectively, Uncover Insights and Master Advanced SQL for Real-world Applications
              Type: main
ResultId 1