Description

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Table of content

Chapter 1: Introducing Visualization and Tableau

• Why Visualization?
• What is Visualization?
• Positioning of Tableau
• Tableau product lines
• File types in Tableau
  • .twb
  • .twbx
  • .tds
  • .tdsx
  • .tde
  • .tbm

Chapter 2: Working with Single and Multiple Data Sources

• Desktop Architecture
• Data Connection Page
• Connect to a File
  • Excel
  • Open with legacy connection
    • Text
    • Microsoft Access
    • R data file (.rdata)

Connect to a Server

• Microsoft SQL Server
• MySQL
• NoSQL Databases (MongoDB, Cassandra)

Metadata GridUsing Data ExtractsAll about JoinsUsing Custom SQLUsing Data Blending

Chapter 3: Simplifying and Sorting your Data

• Filtering on dimensions and measures
• Soring on single dimension - Primary sort
• Sorting on more than one dimension - Secondary Sort
• Slicing your data by date
  • Discrete dates
  • Continuous dates
• Organizing your data
  • Groups
  • Hierarchies
  • Sets
    • Static sets
    • Dynamic sets
    • Difference between groups and sets

Chapter 4: Measure Values and Measure Names

• Using measure values and measure names in a view

Chapter 5: Using Quick Table Calculations in Tableau

• Running Total
• Percent of Total
• Percentile
• Rank
• Moving average
• Year over Year Growth
• Level Of Detail (LOD) calculations

Chapter 6: Customizing your Data

• String Calculations
• Number Calculations
• Date Calculations
• Logical Calculations

Chapter 7: Statistics

• Descriptive Statistics
  • Sum
  • Average
  • Min
  • Max
  • Count
  • Count(distinct)
  • Median
  • Standard Deviation
  • Variance
• Using the Analytics Pane
  • Constant Lines
  • Average Lines
  • Five magical number summary
    • Box and whisker plot
      • Trend Lines
      • Forecast

Chapter 8: Chart Forms

• Bar Chart
• Pie chart
• Line graph
• Scatter Plot
• Histogram
• Heat Map
• Tree Map
• Highlight Table

Chapter 9: Advance Visualization Methods

• Waterfall Charts
• Gantt View
• Bullet Graph

Chapter 10: Dashboard and Stories

• Creating an interactive dashboard
• Adding Actions to your dashboard
• Telling stories with data

Chapter 11: Integration of R with Tableau

Functions such as (SCRIPT_INT(), SCRIPT_REAL(), SCRIPT_BOOL(), SCRIPT_STR())Data Mining

• Affinity Analysis
• K-means Clustering

About the Author

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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.Subhashini Chellappan is a Software Engineering Team Lead with the talent division of Accenture. She has rich experience in both academia and the software industry.She has published couple of papers in various Journals and Conferences.Her areas of interest and expertise are centered on Business Intelligence, Big Data and Analytics technologies such as Hadoop, NoSQL Databases, Spark and Machine Learning.