Pro Tableau: A Step-by-Step Guide

Leverage the power of visualization in business intelligence and data science to make quicker and better decisions. Use statistics and data mining to make compelling and interactive dashboards. This book will help those familiar with Tableau software chart their journey to being a visualization expert.

Pro Tableau demonstrates the power of visual analytics and teaches you how to:

• Connect to various data sources such as spreadsheets, text files, relational databases (Microsoft SQL Server, MySQL, etc.), non-relational databases (NoSQL such as MongoDB, Cassandra), R data files, etc.
  
• Write your own custom SQL, etc.
  
• Perform statistical analysis in Tableau using R
  
• Use a multitude of charts (pie, bar, stacked bar, line, scatter plots, dual axis, histograms, heat maps, tree maps, highlight tables, box and whisker, etc.)
  

What you’ll learn

• Connect to various data sources such as relational databases (Microsoft SQL Server, MySQL), non-relational databases (NoSQL such as MongoDB, Cassandra), write your own custom SQL, join and blend data sources, etc.
  
• Leverage table calculations (moving average, year over year growth, LOD (Level of Detail), etc.
  
• Integrate Tableau with R
  
• Tell a compelling story with data by creating highly interactive dashboards
  

Seema Acharya is a Lead Principal with the Education, Training and Assessment department of Infosys Limited. She is an educator by choice and vocation, and has rich experience in both academia and the software industry. She is also the author of the books, “Fundamentals of Business Analytics”, ISBN: 978-81-265-3203-2, publisher – Wiley India and “Big Data and Analytics”, ISBN: 9788126554782, publisher – Wiley India. She has co-authored a paper on “Collaborative Engineering Competency Development” for ASEE (American Society for Engineering Education). She holds the patent on “Method and system for automatically generating questions for a programming language”. Her areas of interest and expertise are centered on Business Intelligence, Big Data and Analytics technologies such as Data Warehousing, Data Mining, Data Analytics, Text Mining and Data Visualisation.