Jun Shan – författare

Take your first steps to becoming a fully qualified data analyst by learning how to explore complex datasetsKey FeaturesMaster each concept through practical exercises and activitiesDiscover various statistical techniques to analyze your dataImplement everything you’ve learned on a real-world case study to uncover valuable insightsBook DescriptionEvery day, businesses operate around the clock, and a huge amount of data is generated at a rapid pace. This book helps you analyze this data and identify key patterns and behaviors that can help you and your business understand your customers at a deep, fundamental level.SQL for Data Analytics, Third Edition is a great way to get started with data analysis, showing how to effectively sort and process information from raw data, even without any prior experience.You will begin by learning how to form hypotheses and generate descriptive statistics that can provide key insights into your existing data. As you progress, you will learn how to write SQL queries to aggregate, calculate, and combine SQL data from sources outside of your current dataset. You will also discover how to work with advanced data types, like JSON. By exploring advanced techniques, such as geospatial analysis and text analysis, you will be able to understand your business at a deeper level. Finally, the book lets you in on the secret to getting information faster and more effectively by using advanced techniques like profiling and automation.By the end of this book, you will be proficient in the efficient application of SQL techniques in everyday business scenarios and looking at data with the critical eye of analytics professional.What you will learnUse SQL to clean, prepare, and combine different datasetsAggregate basic statistics using GROUP BY clausesPerform advanced statistical calculations using a WINDOW functionImport data into a database to combine with other tablesExport SQL query results into various sourcesAnalyze special data types in SQL, including geospatial, date/time, and JSON dataOptimize queries and automate tasksThink about data problems and find answers using SQLWho this book is forIf you're a database engineer looking to transition into analytics or a backend engineer who wants to develop a deeper understanding of production data and gain practical SQL knowledge, you will find this book useful. This book is also ideal for data scientists or business analysts who want to improve their data analytics skills using SQL.Basic familiarity with SQL (such as basic SELECT, WHERE, and GROUP BY clauses) as well as a good understanding of linear algebra, statistics, and PostgreSQL 14 are necessary to make the most of this SQL data analytics book.

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.