Tableau 10 and Tableau 9.3 Desktop, Server & Data Science
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Tableau 10 and Tableau 9.3 Desktop, Server & Data Science

Learn the science & art behind creating powerful reports, dashboards to solve amazing & difficult business problems
Best Seller
3.8 (240 ratings)
Instead of using a simple lifetime average, Udemy calculates a course's star rating by considering a number of different factors such as the number of ratings, the age of ratings, and the likelihood of fraudulent ratings.
1,964 students enrolled
Created by ExcelR Solutions
Last updated 9/2017
Current price: $10 Original price: $200 Discount: 95% off
5 hours left at this price!
30-Day Money-Back Guarantee
  • 30.5 hours on-demand video
  • 2 Articles
  • 9 Supplemental Resources
  • Full lifetime access
  • Access on mobile and TV
  • Certificate of Completion
What Will I Learn?
  • Learn about data visualisation principles & importance of Tableau in present world
  • Learn about Tableau Architecture & the top charts used in Tableau
  • Learn about the statistical concepts pivotal for success in Tableau profession
  • Learn about building prediction models & forecasting models in Tableau
  • Learn about Tableau calculated fields & advanced reporting concepts
  • Learn in-depth concepts of K-Means clustering & Text Mining & how to accomplish the same in Tableau
  • Learn about various Tableau Server concepts including security settings, automatic reporting, etc.
View Curriculum
  • Download all the datasets provided as part of this program to be able to practice & replicate the visualisations
  • Download Tableau Desktop Professional software from Tableau website
  • This course is about learning Business Intelligence & Analytical tool called Tableau, which has been in leaders position since 4 years
  • Business Intelligence, Analytics, Data Visualisation, Tableau desktop, Tableau server, Tableau & Hadoop, Tableau & R, are the common terminologies used to find this course
  • We have included course content in form of powerpoint presentation, datasets used for visualisation, 2 live case study projects for download, interview questions, sample resumes/profiles for job seekers
  • This course is extremely exhaustive & hence will last for more than 25 hours
  • Course is structured to start with introduction to the tool & the principles behind data visualisation. From there Tableau desktop is explained thoroughly including analytical concepts behind applicable visualisation. Finally course ends with explanation on Tableau server & the final 2 use cases as projects along with interview questions for job seekers
  • Jobs are abundant for Tableau & salaries are very promising & highest in this domain. Also this course is very exhaustive which includes Statistics, Forecasting, Regression models, K-means Clustering, Text Mining, Hadoop & R required for Tableau. Also included are Tableau Desktop & Server concepts in one course. 
Who is the target audience?
  • With plethora of job opportunities & luring salaries which are best in industry, Tableau promises to be one of the best professions which is most sort after by students & working professionals. This course is meant for students, working professionals, data warehouse & business intelligence professionals, data analysts, data scientists, etc., who want to learn the science & art behind generating powerful data visualisations, to address even difficult business problems. Prior knowledge of working with data is a plus but not mandatory.
Compare to Other Tableau Courses
Curriculum For This Course
143 Lectures
Tableau Introduction
12 Lectures 01:33:43

Brief introduction about the trainer and overall Agenda of this program. Happy learning!

Preview 07:04

Learn about the concepts that would be discussed as part of this section. Learn on why Tableau is extremely valid to be in the current world alongside learning Tableau's dominance in the space of Business Intelligence & Analytics. You will notice that Tableau exists in the leaders quadrant of Gartner's magic quadrant since 4 years in a stretch.

Preview 05:39

Learn about Tableau and its importance in the space of Analytics. Learn on why data visualization is extremely imperative in the world of big data. Get a glimpse into the amount of data getting generated via various sources. Finally you will learn the importance of data visualization in identifying interesting insights from the data.

Tableau, Analytics - Ice breaker

Learn about the various products which Tableau provides us to cater to our business needs. This includes Tableau Desktop, Server, Online, Mobile, Public, Reader. Learn about the Tableau architecture and various components including various data source formats, data connectors and APIs.

Preview 10:17

Learn about the various components of Tableau server including Data Server, VizQL Server, Application Server. Learn about the load balancing and failover support with Tableau. Also learn on what are the various browsers, mobile devices on which end users can view the visualization using Tableau

Tableau Architecture Part 2

Learn on how to extract the data from various datasources using Tableau Desktop or Tableau Server. Also discussed about is the way to establish live connection with data sources using Tableau Desktop & Server. Learn on how we can extract inly relevant fields of the data source by writing queries. One can also automate the reports & establish security settings in Tableau.

Tableau Architecture Part 3

Learn about how to download and install tableau desktop 

How to download and install tableau

Learn about the operating systems on which Tableau Desktop can be installed. Pros and Cons of using it on the two operating systems. Also learn about VSA of Tableau, the word coined by ExcelR Solutions. 

An Introduction to Tableau Desktop and History of Tableau

Learn about Tableau start page & how to connect to wide variety of various datasources. Also learn about thumbnails & discover pane, which will help you gain access to amazing real-world projects which are solved in current world. 

Explore Tableau "Start Page"

Learn about an interesting case study solved using data visualisation using Tableau, which is called as Location Based Analytics. 

Location Based Analytics using Tableau

Learn about the worksheet interface of Tableau including dimensions & measures. Learn on how to covert dimensions to measures & vice-versa. Learn about the terminologies of various components of a worksheet & about show me panel. 

Preview 13:24

Learn on how to accomplish a simple visualisation on Bar plot, function of Filters & Marks shelf. Also learn about the usage of double clicking on measures & dimensions. 

Basic Tableau Visualization

7 questions
Statistics for Tableau including Linear Regression, K-Means Clustering & R
26 Lectures 06:34:07

Learn about the basic statistics required to get started with Tableau. As part of this learn about the very first question which any management person would ask pertaining to business. Learn about the measures of central tendency. 

Preview 16:18

Learn about the basic statistics required to get started with Tableau. As part of this learn about the very second question which any management person would ask pertaining to business. Learn about the second moment business decision. 

Measures of Dispersion

Learn about the science behind using Bar plot & Histogram. One should know about the applications & uses of each visualisation before accomplishing a specific chart.

Barplot & Histogram

Learn about the various components of Box Plot & how to identify the outliers using this plot. Also learn about the quartiles, IQR, median, etc., of Box Plot. 

Box Plot

Learn about how to accomplish a simple visualisation using Bar plot & learn on how to make the visualisation tell different stories using a Bar plot by simply dragging the various dimensions & measures around on a worksheet.

Tableau-Barplot, Color encoded, Nested, Stacked

Learn about the steps involved in generating histograms. Also learn about what kind of inferences can be drawn using histogram and explore the opportunities of skewness & thereby long tail effect.


Learn about steps involved in generating histogram by changing the number of bins. Experimenting by changing the bins in histogram, to derive meaningful insights, is pivotal to the success of drawing business inferences. 

Histogram-Calculated Field

Learn about the famous 80/20 rule, which says that 80% of problems are because of 20% of causes. Learn about how to generate a Pareto chart & how to draw reference lines. 

Pareto Chart

Learn about the famous 80/20 rule, which says that 80% of problems are because of 20% of causes. Learn about how to generate a Pareto chart & how to plot a curved line graph on top of the bar plot.

Overlaying Pareto Chart

Learn about the steps involved in generating Bar Plots by having two axis instead of one. This is accomplished using a concept called as dual axis. 

Barplot Dual Axis

Learn about the steps involved in creating a calculated field & using this to generate a Bar Plot for comparison. 

Barplot-Calculated Field

Learn about the steps involved in accomplishing a Box Plot. Interesting part is to learn about the various components of Box Plot and draw meaningful business insights. 

Box Plot

Learn about the concepts behind scatter diagrams, which are used to explain about the direction of relationship, strength of relationship & linearity of relationship between 2 variables. Also learn about how to objective way of evaluating strength of relationship using correlation coefficient value. 

Scatter Diagram, Correlation Coefficient

Learn about the concepts of Population & Sample, how to determine sample size. Also learn about calculating the confidence interval using a real world case-study.

Confidence Interval-Part 1

Learn about the various ways of generating scatter plot & how to draw inferences from the scatter plot in Tableau.

Scatter Plot using Tableau

Learn using R on how to generate the Z value & how to manually calculate the confidence intervals using Z-distribution & t-distribution. 

Confidence Interval-Part 2

Learn about simple linear regression concepts and various components which one needs to understand before building prediction models. Also learn about a real world case-study from Life Sciences Health Care industry to understand about building prediction model.

Preview 18:33

Learn about the use of R in building prediction model to understand on how to build an equation for prediction. Also learn on how to gage the strength of the model along with the possible transformations to improve the accuracy of the model. 

Simple Linear Regression R

Learn on how to build simple linear regression using Tableau Analytics pane. Also learn about the log transformation option of Tableau to see whether the accuracy of the model increases. 

Preview 08:41

Learn about exponential & polynomial regression using Tableau. Learn about how to bring back the log of output variable to the original variable by taking exponential. Also learn about how will changing the degrees impact the polynomial regression. 

Linear Regression Tableau-Part 2

Learn about the data visualisation principles which are pivotal for successful reports generation. In order to gain the attention of the stakeholders one has to ensure that visualisation is done based on Tufte's principles, Lie Factor, etc.

Preview 14:30

Learn about the data visualization principles including consistent scales, standardized monetary values, presenting data in context, data-ink ratio, chart junks, Moire effect & Necker illusion. 

Data Visualization Principles-Part 2

Learn about how to connect to a Microsoft Access data source using Tableau. Also learn about establishing connection between R and Tableau in a Windows machine. 

Connecting to Data R

Learn on how to establish a connection between R and Tableau on a Macintosh Machine. Also learn about how to accomplish K-means clustering using Tableau by having a connection established with R.

Preview 14:22

Learn about what is clustering and why K-means clustering is such an important technique within Data Mining Unsupervised learning. 

Preview 34:28

Learn about K-Means clustering using R code and understand the output in finer details. 

K-means Clustering -Part 2

8 questions
Working with Data using Tableau including Data Extraction & Blending
6 Lectures 01:22:23

Learn about the new feature of Tableau 9.3, which will make the life of most of the analysts simpler by identifying the discrepancies in a dataset and highlighting the auto corrections which have been made by Tableau automatically. 

Data Interpreter-Pivot

Learn about how to change the data types within Tableau from dimensions to measures. Also learn about customising the different views along with Split function of Tableau. 

Customizing Views, Data Types, Fields

Learn about how to use clipboard features in Tableau, how hierarchies are created & changed. Also learn about how to save the metadata and how to share it. 

Using Clipboard, Hierarchies, Saving -Sharing Metadata

Learn about how to extract data from various data sources and how to refresh the changes, either incrementally or fully. 

Data Extraction

Learn about how to work with multiple data sources at one go. Also learn about how to use different fields from the various data sources to accomplish a visualisation to solve business problems. 

Preview 12:28

Learn about the integration between Cloudera Hadoop and Tableau. Also learn about how to extract the data from Twitter using Tableau.

Tableau Hadoop Integration & Twitter data Extraction using Tableau

Quiz 3
9 questions
Various Charts in Tableau including Text Mining
11 Lectures 01:58:19

Learn about when to use trend line chart as part of time series analysis. Also learn about the visualisations pertaining to line chart which will help the business answer a wide variety of questions. 

Trend Line Chart

Learn about the various mark types in maps using case studies. Learn about creating pie charts on maps and ranking states by sales using maps. 

Tableau_Maps_Mark Types

Learn about generating a basic line chart and from there on learn about the advanced line chart using multiple panes in Tableau. Also learn about using calculated field while using a line chart.

Line Chart Variants

Learn about two basic yet powerful default charts used in Tableau. Text table is to visualise the data in textual format. Also learn about the 2 variants of Area chart including discrete & continuous. 

Text Table - Area Chart

Learn about the Highlight table, Heat Maps, how to change the colors, filtering and Circle plots, Tree maps & how to draw interesting insights. 

Various Charts-Part 1

Learn about the Pie Chart and the use of this in various scenarios. Dos and Don'ts of the Pie chart are extremely imperative because this chart should be sparingly used in real world scenarios. 

Preview 06:33

Learn about the use of Bubble chart. Learn on how to generate this chart using the default options of Tableau and also learn on how to manually generate the same. 

Bubble Chart

Learn about the Bullet chart and how to set the various target values within the chart. Learn about the various shades of colors within this chart and its implications in drawing inferences. 

Bullet Chart

Learn how to make waterfall or Mario chart using a simple calculated field using the example of profit measure of a firm.

Waterfall Chart

Learn about the various options within Analytics pane of Tableau, including reference lines, references bands & reference distributions to visualise the various business parameters.

Reference Lines, Bands, Distributions

Learn about how to generate word cloud, also called as tag cloud, manually using Tableau. There is no default chart for word cloud within Tableau. 

Word Cloud

Quiz 4

Quiz 4
7 questions
Bonus Section...
1 Lecture 20:31

Learn about the science behind generating word clouds & sentiment analysis, including positive & negative word clouds. Also learn about Term Frequency & Term Frequency Inverse Document Frequency, the two key concepts used to generate the word clouds. 

Preview 20:31
Forecasting/Time series/Trend lines in Tableau
14 Lectures 02:47:45

What is forecasting understanding with respective to a time series data, Introduction about the trainer, course agenda for forecasting

Preview 14:18

Learn on why forecasting is so important and a few case studies of forecasting failures. Also learn about the various types of forecasts such as point, interval and density forecasts. 

Forecasting-Why Forecasting & types of Forecasts

Learn on why forecasting is so important and a few case studies of forecasting failures. Also learn about the various types of forecasts such as point, interval and density forecasts. 

Forecasting - Who Forecasts?

Learn about who does the forecasting and about the dataset to be used for forecasting. Also learn about the various notations which are pivotal for strong foundation.

Forecasting Strategy-Defining goal

Learn about the 8 steps in brief for successful forecasting. Also deep dive on the first step which is Defining Goal, which is the single most important step of the 8-step forecasting strategy.

Forecasting-Data Collection,Various components

Learn about step-2, Data collection in the 8-step forecasting strategy. Also you would gain in-depth knowledge on exploring the data series, which happens to be the 3rd step of the 8-step process. 

Forecasting Seasonal, Trend, Random components

Learn the rudimentary visualization used in forecasting; Scatter plot. Time Plot, Lag plot. Understand the correlation function, Standard error for lagged plot

Forecasting-Data Exploration & Visualization

Learn the rudimentary visualization used in forecasting; Scatter plot. Time Plot, Lag plot. Understand the correlation function, Standard error for lagged plot .   

Forecasting-Data Visualization Principles

Understanding forecast error through various plots, various measure of forecast errors and its dichotomies

Forecasting-Error measures

Preliminaries to forecasting; pre–processing, incorporating additional variables, data Partitioning in XL Miner

Exploratory Data Analysis Using Walmart Footfalls Example Part-1

Types of forecasts; Naïve forecast, distribution of error identifying which is more desirable, Old Lecture 142: Evaluating Predictive AccuracyTypes of errors its strengths and weaknesses, challenges with data quality, forecasting prediction interval for normal and non–normal data.

Exploratory Data Analysis Using Walmart Footfalls Example Part-2

Types of errors its strengths and weaknesses, challenges with data quality, forecasting prediction interval for normal and non–normal data.

Evaluating Predictive Accuracy

Introduction to two main methods of forecasting, Choice of the model based on Data Volatility


Forecasting Different Methods

A complete recap of all the topics related to forecasting covered so far

Recap Forecasting Part-1

14 questions
Forecasting Model Based Approaches
10 Lectures 02:28:06

Various model based approaches to forecasting, Performing a linear Model forecast using XL Miner, Walk through the various steps involved in Linear Model.

Forecasting Methods-Linear Model

Walk through the steps in performing exponential forecast, Quadratic forecasting, Additive seasonality forecast using XL Miner

Forecasting Methods-Exponential, Quadratic and Additive Seasonality Models

Walk through the steps in performing Additive seasonality with trend forecast and multiplicative seasonality; Configuring visually the best model and ratifying with the least error model; Combining the training and Validation data to run the final model

Forecasting Methods- Additive seasonality with trend,Multiplicative seasonality

Addressing irregular components, building econometric models based on External information and domain knowledge

Forecasting-Irregular Components.

Forecasting - Linear Regression and Auto Regression

Features of autoregressive models, Detailed study of residuals and its leftover information, Forecasting errors by AR model using the principle of Parcimony, iterative study of ‘residuals of residuals’ till no further information can be gleaned, Building the final model by plugging in the error factor

Forecasting Autocorrelation Model

The disadvantages and limitations of Model Based approaches, the underlying principle of model based and data based approach to forecasting

Forecasting-Model Based Approach VS Data Driven Approach

Computing the Moving average even window width and walk thru of the steps in computing the seasonal indexes, Normalizing the seasonal indexes and drawing inferences for these, computing the de seasoned data using the respective seasonal indexes  

Forecasting-Understanding Moving Average

Naïve technique, Moving average approach with adequate ‘window width’ for smoothing the data, Key takeaways from the moving average approach; two types of calculations for moving averages and the math behind it

Forecast Methods based on Smoothing

Types of Exponential smoothing and their facets, the formula for Simple exponential smoothing considering decreasing weights for older data, understanding under smoothing and over smoothing.

Forecast Methods Exponential Smoothing
Forecast Data Driven Approach
4 Lectures 50:11

Hands on with the Holt’s method with level and trend, hands on with Winter’s method with level trend and seasonality, importance of period for encompassing the seasonality in the Winter’s method, Forecasting using the model with the least error.

Forecast Data Driven- Holts and Winter Method

De-seasoning the data using seasonal indexes and re–seasoning it using the same

Forecast Data Driven-Seasonal Indexes

Computing the Moving average even window width and walk thru of the steps in computing the seasonal indexes, Normalizing the seasonal indexes and drawing inferences for these, computing the de seasoned data using the respective seasonal indexes  

Forecast Seasonal Indexes,Centered Moving Average Hands On

Using the Sine and cosine component predictors for capturing the seasonality for daily data, logit regression using odds, Walk through the steps of using XL Miner for performing the Logistic regression

Forecasting -Logistic Regression using XLminar
Tableau Filtering
7 Lectures 01:16:48

Learn about the 'include' & 'exclude' functionalities of filtering. Learn about relative date, range of dates, starting date, ending date, special & various filtering options on a date dimension. 

Tableau Filtering_Part 1

Learn about the filter options when we filter on dimensions & measures. Also learn about general, wildcard, condition, top. Also learn on how to apply a filter to all worksheets or only a few. 

Tableau Filtering_Part 2

Learn about setting a quick filter and also learn about the various options available to represent the quick filter, including single, multiple value list, dropdown & sliders.

Tableau Quick Filters

Learn about creating a parameter and how to show parameter control to perform what-if analysis.

Preview 08:43

Learn about creating a parameter and how to use it in the calculated field, which can be used to show case the use of Tableau to perform what-if analysis in solving business problems pertaining to setting goals. 

Parameters_Part 2

Learn about filter action, highlight action & URL action through demonstration of the options using Tableau. Also learn about all the various options available in Filter actions.

Tableau Worksheet Actions_Filter Actions

Learn about the Highlight action & the various options are explored thoroughly in this tutorial. Also learn about URL action to navigate to a url in web browser upon clicking a specific entry on the map. 

Preview 09:00

6 questions
Tableau Groups, Sets, Calculations
9 Lectures 02:52:51

Learn on how to create groups within dimensions by directly exploring the 'Create Group' option. Also learn about creating groups using visual grouping by selecting a specific dimensions or all dimensions. 

Dimension Grouping _ Visual Grouping

Learn on how to create sets to narrow the dimensions entries and also learn about how to combine multiple sets to generate a visualisation to solve complex business questions. 

Different Sets in Tableau

Learn about Ad hoc calculations, which are also called as on-the-fly calculations. Also learn about simple numeric calculation & various components of calculation editor. 

Calculated Fields_Adhoc Calculations _ Calculation Editor

Learn about the various Numeric calculations, String calculation including converting the customer name into a proper case, date calculations including creating a default date dimension. 

Calculated Fields_Numeric, String, Date Calculations

Learn about creating logic constructs including IF/ELSEIF/ELSE/END, CASE/WHEN/THEN/ELSE/END, IF/ELSE/END, IF/THEN/ELSE/END, etc.

Calculated Fields_Logic Constructs _ Aggregation

Learn about aggregation within aggregation using LOD expressions. Also learn about the basic syntax of LOD expressions using FIXED scope keyword and Table scoped LOD expression.

Preview 11:53

Learn about the LOD expression scope keywords for aggregation granularity including FIXED LOD expression, INCLUDE & EXCLUDE LOD expressions using business scenarios. 

LOD expressions_Part 2

Learn about the table calculations such as Grand Totals for rows, columns, Percentage of totals. Also learn about Table (Across), Table (Down), Table (Across then Down), Table (Down then Across).

Table Calculations_Part 1

Learn on how to calculate 'Year over Year Growth', 'YTD Total', 'YTD Growth' & 'Compound Growth Rate' using Tableau and also learn on how to calculate the same using spreadsheet.

Table Calculations_Part 2

4 questions
7 More Sections
About the Instructor
ExcelR Solutions
3.9 Average rating
751 Reviews
7,680 Students
8 Courses
Pioneer in professional management trainings & consulting


Certified Six Sigma Master Black Belt

Project Management Professional (PMP)

Agile Certified Practitioner (PMI - ACP)

Risk Management Professional (PMI-RMP)

Certified Scrum Master

Agile Project Management – Foundation & Practitioner from APMG

Bharani Kumar is an Alumnus of premier institutions like IIT & ISB with 15+ years professional experience and worked in various MNCs such as HSBC, ITC, Infosys, Deloitte in various capacities such as Data Scientist, Project Manager, Service Delivery Manager, Process Consultant, Delivery Head etc.

He has trained over 1500 professionals across the globe on Business Analytics, Agile, PMP, Lean Six Sigma, Business analytics and the likes.

He has 8 years of extensive experience in corporate, open house and online training.

He is a thorough implementer with abilities in Business Analytics and Agile projects.

He worked in Delivery management focusing on maximizing business value articulation.

He has a comprehensive experience in leading teams and multiple projects.

Quality Management: A thorough implementer with abilities in Quality management focusing on maximizing customer satisfaction, process compliance and business value articulation; comprehensive experience in leading teams & multiple projects. A result-oriented leader with expertise in devising strategies aimed at enhancing overall organizational growth, sustained profitability of operations and improved business performance.

Project Management: Project Management Professional involved in Initiation, Planning, Execution, Monitoring & Controlling and Closing phases of project activities. Devising and implementing project plans within preset budgets and deadlines and managing the projects towards successful delivery of project deliverables and meeting project objectives.

Training: Close to 8 years training experience and conducted multiple trainings in PMP, Agile, Six Sigma, Business Analytics and Process Excellence across the globe. Understands the individual differences of the attendees and possesses excellent training skills and considered as one of the best trainers in his areas of expertise.