• Comparison and benefits against reading raw numbers
• Real use cases from various business domains
• Some quick and powerful examples using Tableau without going into the technical details of Tableau
• Installing Tableau
• Tableau interface
• Connecting to Data Source
• Tableau data types
• Data preparation

• Installation of Tableau
• Desktop Architecture of Tableau
• The interface of Tableau (Layout, Toolbars, Data Pane, Analytics Pane, etc.)
• How to start with Tableau
• The ways to share and export the work done in Tableau

Hands-on Exercise:

• Play with Tableau desktop
• Learn about the interface
• Share and export existing works

• Connection to Excel
• Cubes and PDFs
• Management of metadata and extracts
• Data preparation
• Joins (Left, Right, Inner, and Outer) and Union
• Dealing with NULL values, cross-database joining, data extraction, data blending, refresh extraction, incremental extraction, how to build extract, etc. 

Hands-on Exercise:

• Connect to Excel sheet to import data
• Use metadata and extracts
• Manage NULL values
• Clean up data before using
• Perform the join techniques
• Execute data blending from multiple sources

• Mark, highlight, sort, group, and use sets (creating and editing sets, IN/OUT, sets in hierarchies)
• Constant sets
• Computed sets, bins, etc.

Hands-on Exercise:

• Use marks to create and edit sets
• Highlight the desired items
• Make groups
• Apply sorting on results
• Make hierarchies among the created sets

• Filters (Addition and removal)
• Filtering continuous dates, dimensions, and measures
• Interactive Filters, marks card, and hierarchies
• How to create folders in Tableau
• Sorting in Tableau
• Types of sorting
• Filtering in Tableau
• Types of filters
• Filtering the order of operations

Hands-on Exercise:

• Use the data set by date/dimensions/measures to add a filter
• Use an interactive filter to view the data
• Customise/remove filters to view the result

• Using Formatting Pane to work with menu, fonts, alignments, settings, and copy-paste
• Formatting data using labels and tooltips
• Edit axes and annotations
• K-means cluster analysis
• Trend and reference lines
• Visual analytics in Tableau
• Forecasting, confidence interval, reference lines, and bands

Hands-on Exercise:

• Apply labels and tooltips to graphs, annotations, edit axes’ attributes
• Set the reference line
• Perform k-means cluster analysis on the given dataset

• Working on coordinate points
• Plotting longitude and latitude
• Editing unrecognised locations
• Customising geocoding, polygon maps, WMS: web mapping services
• Working on the background image, including add image
• Plotting points on images and generating coordinates from them
• Map visualisation, custom territories, map box, WMS map
• How to create map projects in Tableau
• Creating dual axes maps and editing locations

Hands-on Exercise:

• Plot longitude and latitude on a geo map
• Edit locations on the geo map
• Custom geocoding
• Use images of the map and plot points
• Find coordinates
• Create a polygon map
• Use WMS

• Calculation syntax and functions in Tableau
• Various types of calculations, including Table, String, Date, Aggregate, Logic, and Number
• LOD expressions, including concept and syntax
• Aggregation and replication with LOD expressions
• Nested LOD expressions
• Levels of details: fixed level, lower level, and higher level
• Quick table calculations
• The creation of calculated fields
• Predefined calculations
• How to validate

• Creating parameters
• Parameters in calculations
• Using parameters with filters
• Column selection parameters
• Chart selection parameters
• How to use parameters in the filter session
• How to use parameters in calculated fields
• How to use parameters in the reference line

Hands-on Exercise:

• Creating new parameters to apply on a filter
• Passing parameters to filters to select columns
• Passing parameters to filters to select charts

• Dual axes graphs
• Histograms
• Single and dual axes
• Box plot
• Charts: motion, Pareto, funnel, pie, bar, line, bubble, bullet, scatter, and waterfall charts
• Maps: tree and heat maps
• Market basket analysis (MBA)
• Using Show me
• Text table and highlighted table

Hands-on Exercise:

• Plot a histogram, treemap, heat map, funnel chart, and more using the given dataset.
• Perform market basket analysis (MBA) on the same dataset.

• Building and formatting a dashboard using size, objects, views, filters, and legends
• Best practices for making creative as well as interactive dashboards using the actions
• Creating stories, including the intro of story points
• Creating as well as updating the story points
• Adding catchy visuals in stories
• Adding annotations with descriptions, dashboards, and stories
• What is a dashboard?
• Highlight actions, URL actions, and filter actions
• Selecting and clearing values
• Best practices to create dashboards
• Dashboard examples; using Tableau workspace and Tableau interface
• Learning about Tableau joins
• Types of joins
• Tableau field types
• Saving as well as publishing the data source
• Live vs extract connection
• Various file types 

Hands-on Exercise

• Create a Tableau dashboard view, include legends, objects, and filters
• Make the dashboard interactive
• Use visual effects, annotations, and descriptions to create and edit a story.

• Introduction to Tableau Prep
• How Tableau Prep helps quickly combine join, shape, and clean data for analysis
• Creation of smart examples with Tableau Prep
• Getting deeper insights into the data with a great visual experience
• Making data preparation simpler and accessible
• Integrating Tableau Prep with Tableau analytical workflow
• Understanding the seamless process from data preparation to analysis with Tableau Prep

• Introduction to the R language
• Applications and use cases of R
• Deploying R on the Tableau platform
• Learning R functions in Tableau
• The integration of Tableau with Hadoop

Hands-on Exercise:

• Deploy R on Tableau
• Create a line graph using the R interface
• Connect Tableau with Hadoop to extract data

• HR: Analyse the Attrition rate of Employees
• Sales: Predicting Department wise Sales
• Multi-Domain: Business Analytics Optimization
• Marketing: Website Trend Analysis
• Financial Analysis: Stock Market Prediction
• Finance: Analyse ETF Trends