Install data analytics into your brain with this comprehensive introduction
Data Analytics & Visualization All-in-One For Dummies collects the essential information on mining, organizing, and communicating data, all in one place. Clocking in at around 850 pages, this tome of a reference delivers eight books in one, so you can build a solid foundation of knowledge in data wrangling. Data analytics professionals are highly sought after these days, and this book will put you on the path to becoming one. You'll learn all about sources of data like data lakes, and you'll discover how to extract data using tools like Microsoft Power BI, organize the data in Microsoft Excel, and visually present the data in a way that makes sense using a Tableau. You'll even get an intro to the Python, R, and SQL coding needed to take your data skills to a new level. With this Dummies guide, you'll be well on your way to becoming a priceless data jockey.
Mine data from data sources
Organize and analyze data
Use data to tell a story with Tableau
Expand your know-how with Python and R
New and novice data analysts will love this All-in-One reference on how to make sense of data. Get ready to watch as your career in data takes off.
Sprache
Verlagsort
Verlagsgruppe
Maße
Höhe: 234 mm
Breite: 188 mm
Dicke: 46 mm
Gewicht
ISBN-13
978-1-394-24409-6 (9781394244096)
Copyright in bibliographic data and cover images is held by Nielsen Book Services Limited or by the publishers or by their respective licensors: all rights reserved.
Schweitzer Klassifikation
This All-in-One draws on the work of top authors in the For Dummies series who've created books designed to help data professionals do their work. The experts are Jack Hyman, Luca Massaron, Paul McFedries, John Paul Mueller, Lillian Pierson, Jonathan Reichental PhD, Joseph Schmuller PhD, Alan Simon, and Allen G. Taylor.
Autor*in
Thinking Helmet, Inc.
Database Consultant, Oregon City, Oregon
Introduction 1
Book 1: Learning Data Analytics & Visualizations Foundations 7
Chapter 1: Exploring Definitions and Roles 9
Chapter 2: Delving into Big Data 19
Chapter 3: Understanding Data Lakes 41
Chapter 4: Wrapping Your Head Around Data Science 51
Chapter 5: Telling Powerful Stories with Data Visualization 81
Book 2: Using Power BI for Data Analytics & Visualization 107
Chapter 1: Power BI Foundations 109
Chapter 2: The Quick Tour of Power BI 123
Chapter 3: Prepping Data for Visualization 141
Chapter 4: Tweaking Data for Primetime 167
Chapter 5: Designing and Deploying Data Models 183
Chapter 6: Tackling Visualization Basics in Power BI 203
Chapter 7: Digging into Complex Visualization and Table Data 227
Chapter 8: Sharing and Collaborating with Power BI 247
Book 3: Using Tableau for Data Analytics & Visualization 265
Chapter 1: Tableau Foundations 267
Chapter 2: Connecting Your Data 285
Chapter 3: Diving into the Tableau Prep Lifecycle 313
Chapter 4: Advanced Data Prep Approaches in Tableau 337
Chapter 5: Touring Tableau Desktop 351
Chapter 6: Storytelling Foundations in Tableau 371
Chapter 7: Visualizing Data in Tableau 391
Chapter 8: Collaborating and Publishing with Tableau Cloud 425
Book 4: Extracting Information with SQL 443
Chapter 1: SQL Foundations 445
Chapter 2: Drilling Down to the SQL Nitty-Gritty 455
Chapter 3: Values, Variables, Functions, and Expressions 487
Chapter 4: SELECT Statements and Modifying Clauses 513
Chapter 5: Tuning Queries 539
Chapter 6: Complex Query Design 557
Chapter 7: Joining Data Together in SQL 591
Book 5: Performing Statistical Data Analysis & Visualization with R Programming 605
Chapter 1: Using Open Source R for Data Science 607
Chapter 2: R: What It Does and How It Does It 623
Chapter 3: Getting Graphical 651
Chapter 4: Kicking It Up a Notch to ggplot2 671
Book 6: Applying Python Programming to Data Science 689
Chapter 1: Discovering the Match between Data Science and Python 691
Chapter 2: Using Python for Data Science and Visualization 703
Chapter 3: Getting a Crash Course in Matplotlib 721
Chapter 4: Visualizing the Data 739
Index 761
