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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

Who this book is for

All levels of IT professionals, from executives responsible for determining IT strategies to systems administrators, to data analysts, to decision makers responsible for driving strategic initiatives, etc. The book will help those familiar with Tableau software chart their journey to a visualization expert.

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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 Grid
Using Data Extracts
All about Joins
Using Custom SQL
Using 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

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