Introduction and Getting Started

• Why Tableau? Why Visualization?
• The Tableau Product Line
• History of tableau
• Level Setting – Terminology
• Getting Started – creating some powerful visualizations quickly
• tableau installation
• tableau architecture
• Different product of tableau
• Live Connections data Data Extracts

Data types and Terms use in tableau:

• Review of some Key Fundamental Concepts: Dimensions and measures
• Row level, aggregate level,
• table level ,Continuous and discrete
• measure name, measure value
• Terminology and Definitions
• Tableau Work Space
• Files and Folders
• Understanding Tableau’s data handling engine, hyper
• Tableau file Extension
• Pivot data
• Data Hierarchies

Joining and Blending Data, PLUS: Dual Axis Charts

• Understanding how LEFT, RIGHT, INNER, and OUTER Joins Work
• Joins With Duplicate Values
• Joining on Multiple Fields
• The Showdown: Joining Data V/s  Blending Data in Tableau
• Data Blending in Tableau
• Dual Axis Chart
• Creating Calculated Fields in a Blend (Advanced Topic)
• Joining and Blending Data, PLUS: Dual Axis Charts

Advanced Dashboards, Storytelling

• Downloading the Dataset and Connecting to Tableau
• Mapping: how to Set Geographical Roles
• Creating Table Calculations for Gender
• Creating Bins and Distributions For Age
• Leveraging the Power of Parameters
• How to Create a Tree Map Chart
• Creating a Customer Segmentation Dashboard
• Advanced Dashboard Interactivity

Advanced Table Calculations

• Project Brief: Coal Terminal Utilization Analysis
• Creating Multiple Joins in Tableau
• Calculated Fields vs Table Calculations
• Creating Advanced Table Calculations
• Saving a Quick Table Calculation
• Specifying Direction of Computation
• Writing your own Table Calculations
• Adding a Second Layer Moving Average
• Quality Assurance For Table Calculations
• Trend lines for Power-Insights
• Creating a Storyline
• Executive Report is Ready
• Advanced Table Calculations

Building Advanced Chart Types and Visualizations / Tips & Tricks

• Bar in Bar
• What are Box and Whisker Plots
• Bullet Chart
• Custom Shapes
• Pie Chart
• ButterFly chart
• Gantt Chart
• Heat Map
• Pareto Chart
• Spark Line
• KPI Chart
• What are Water Fall Charts
• Using Reference Lines and Reference Bands
• Using Combination Charts
• How to Use Dual Charts
• Word cloud
• Funnel Chart
• Using Motion Charts

Best Practices in Formatting and Visualizing

• Formatting Tips
• Drag to Legend
• Edit Legend
• Highlighting
• Labeling
• Legends
• Working with Nulls
• Table Options
• Annotations and Display Options
• Introduction to Visualization Best Practices

Groups and Sets

• Working with Groups
• Creating Static Set
• Creating Dynamic Set
• Combining Sets
• Controlling Sets With Parameters
• Level Of Detail Calculations (LOD)
• Aggregation and Granularity (refresher)
• LOD Calculations Intuition
• LOD Type 1: INCLUDE
• Understanding ATTR() in Tableau
• LOD Type 2: EXCLUDE (Part 1)
• LOD Type 2: EXCLUDE (Part 2)
• Multiple fields in an LOD Calculation
• LOD Type 3: FIXED
• Finalizing the Visualization
• Level Of Detail Calculations

Tableau Maps

• Tableau Maps Introduction & Geographic Roles
• Tableau_Maps Custom Geocoding
• Tableau Maps_Navigating Maps & Map Search
• Tableau Maps_Map Options & Web Map Services
• Tableau_Maps_Background Images

TABLEAU FOR DATASCIENCE

• Statistics for Tableau including Linear Regression, K-Means Clustering & R
• Measures of Dispersion
• Barplot & Histogram
• Box Plot
• Tableau-Barplot, Color encoded, Nested, Stacked
• Histograms
• Histogram-Calculated Field
• Pareto Chart
• Overlaying Pareto Chart
• Barplot Dual Axis
• Barplot-Calculated Field
• Box Plot
• Scatter Diagram, Correlation Coefficient
• Confidence Interval-Part 1
• Scatter Plot using Tableau
• Confidence Interval-Part 2
• Simple Linear Regression
• Simple Linear Regression R
• Linear Regression Tableau-Part 1
• Linear Regression Tableau-Part 2
• Data Visualization Principles-Part 1
• Data Visualization Principles-Part 2
• Connecting to Data R
• Tableau – R connection
• K-means Clustering -Part 1
• K-means Clustering -Part 2

Forecasting/Time series/Trend lines in Tableau

• Forecasting using Tableau
• Forecasting-Why Forecasting & types of Forecasts
• Forecasting – Who Forecasts?
• Forecasting Strategy-Defining goal
• Forecasting-Data Collection,Various components
• Forecasting Seasonal, Trend, Random components
• Forecasting-Data Exploration & Visualization
• Forecasting-Data Visualization Principles
• Forecasting-Error measures
• Exploratory Data Analysis Using Walmart Footfalls Example Part-1
• Exploratory Data Analysis Using Walmart Footfalls Example Part-2
• Evaluating Predictive Accuracy
• Forecasting Different Methods
• Recap Forecasting Part-1

Forecasting Model Based Approaches

• Forecasting Methods-Linear Model
• Forecasting Methods-Exponential, Quadratic and Additive Seasonality Models
• Forecasting Methods- Additive seasonality with trend,Multiplicative seasonality
• Forecasting-Irregular Components.
• Forecasting Autocorrelation Model
• Forecasting-Model Based Approach VS Data Driven Approach
• Forecasting-Understanding Moving Average
• Forecast Methods based on Smoothing
• Forecast Methods Exponential Smoothing
• Forecast Data Driven Approach
• Forecast Data Driven- Holts and Winter Method
• Forecast Data Driven-Seasonal Indexes
• Forecast Seasonal Indexes,Centered Moving Average Hands On
• Forecasting -Logistic Regression using XLminar

DataWearHouse Concept For Business Intelligence

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We Will Be Updated Soon.

We Will Be Updated Soon.