Tableau Training and Certification Course

1. Introduction to the Tableau architecture
2. Working with Tableau dashboard
3. Implementing data blending and aggregation
4. Data visualization and real-time analytics
5. Tableau generated fields and special fields
6. Connecting Tableau with R
7. Deploying R scripts on Tableau
8. Data connections for organizing data
9. Tableau graphs, reports, and calculations

• Data Scientists, Business Intelligence Professionals, and Testing Professionals
• Statisticians, Business Analysts, and Project Managers
• Data Visualization Analysts and Functional Experts
• Graduates and professionals looking to move into the analytics domain

There are no prerequisites for taking up this Tableau certification training course.

• Global Business Intelligence and Analytics market will expand to US$22.8 billion in the next two years – Gartner
• Tableau’s average salary is 77% higher than all other job profiles – Indeed
• Tableau ranks first in the leader quadrant of the Gartner Magic Quadrant of BI for the fourth consecutive year – Gartner

Not only is the demand for Tableau experts great, but it also offers huge returns. Tableau Developers have an average annual salary of US$112,000 in the US and ₹900,000 in India. Tableau is a full Business Intelligence (BI) platform, where anyone can quickly view, search, and analyze data. With Tableau, you can connect to the data you need, whether it’s a small database, big data, or cloud data. Also, with its exclusive drag-and-drop functionality, you can easily spot the trends and outliers.

After completing Intellipaat’s Tableau online training course, you will be able to analyze the business of your company and help in developing highly insightful information.

Tableau is one of the most popular Business Intelligence (BI) and data visualization tools today. It is a complex BI tool but by enrolling for Intellipaat’s Tableau training, you will get to learn it by Tableau experts who will help you learn it easily. You will work on assignments and exercises based on the modules which helps you to apply the concepts in real-life and enhance your learning. You will also work on real-world projects which will give you hands-on experience and substantiate your learning.

Once you join the course, throughout the training you will work on real-time industry-based projects and gain hands-on experience in working in Tableau. There are about 4 real-world Tableau projects that you have to work on in order to successfully complete this online training and receive the course completion certification.

This tableau certification program is conducted by instructors. There is about 30 hours of instructor-led lecture that you will cover in this course. The course also provides self-paced videos of about 16 hours which will help you learn and understand the course at your own pace. The amount of time that you will spend on the module exercises and the four industry-based projects will be around 32 hours. There is no specific time limit as to when you will complete the course but if you are able to follow the lectured conducted by the instructor on a regular basis and complete the required exercises and projects on time then you should be able to complete the Tableau certification in a month.

All of our trainers are experts in Tableau from leading industries. They are Tableau certified professionals who have a lot of experience in this field. All of them are Tableau professionals with SMEs from major organizations and worked in Tableau for a really long time with valuable knowledge in it.

Throughout the course of Tableau certification, you will get industry-specified assignments and exercises at the end of each module. You will get to use the concepts of each modules you have learned in those exercises. These exercises are designed to prepare you for Tableau certification exam. While working on the exercises, you will be able to revise and recall the concepts of all course modules which will help you clear the certification exam without much trouble.

The online Tableau certification course costs about US$ 290 for online training and about US$ 165 for self-paced training. The online training is led by instructors who are experts in this field. It is conducted on a regular basis wherein you can use the online forum to interact with the trainer and clear your doubts. However, if you do not have the time to attend this training on a regular basis and you want to go about the course at your own pace then you can sign up for self-paced training in which you will get the necessary material and the video lectures throughout your lifetime. With the help of self-paced training material, you can take your own time to complete the course and receive your certification.

One of the best things about Tableau is that you do not need to have any prior knowledge in technical and programming languages. However, in order to learn Tableau and become a successful Tableau professional, you need to be good at analytics. You should just be able to understand the dissection of data and have good analytical skills.

What is data visualization?, 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 DataSource, Tableau data types, and data preparation.

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

Hands-on Exercise: Play with Tableau desktop, learn about the interface, and 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 , etc.

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, and make hierarchies among the created sets.

Filters (addition and removal), filtering continuous dates, dimensions, and measures, interactive filters, marks card, hierarchies, how to create folders in Tableau, sorting in Tableau, types of sorting, filtering in Tableau, types of filters, filtering the order of operations, etc.

Hands-on Exercise: Use the data set by date/dimensions/measures to add filter, use interactive filter to view the data, customize/remove filters to view the result, etc.

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, and perform k-means cluster analysis on the given dataset.

Working on coordinate points, plotting longitude and latitude, editing unrecognized locations, customizing 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 visualization, 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, and 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, and 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 reference line, etc.

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, etc.

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; and text table and highlighted table.

Hands-on Exercise: Plot a histogram, tree map, heat map, funnel chart, and more using the given dataset and also 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 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 data source, live vs extract connection, and various file types.

Hands-on Exercise: Create a Tableau dashboard view, include legends, objects, and filters, make the dashboard interactive, and use visual effects, annotations, and description s 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 great visual experience, making data preparation simpler and accessible, integrating Tableau Prep with Tableau analytical workflow, and understanding the seamless process from data preparation to analysis with Tableau Prep.

Introduction to R language, applications and use cases of R, deploying R on the Tableau platform, learning R functions in Tableau, and the integration of Tableau with Hadoop.

Hands-on Exercise: Deploy R on Tableau, create a line graph using R interface, and also connect Tableau with Hadoop to extract data.

Project 1: Working with Tableau Interactive Dashboard

Domain: Sales

Problem Statement: How to make an interactive dashboard with Tableau?

Description:

Upon the completion of this project, you will understand how to create a single point of access for all your sales data, ways of dissecting and analyzing sales from multiple angles, coming up with a sales strategy for improved business revenues.

Project 2: Tableau for Crime Statistics Analysis

Domain: Crime Statistics (Public Domain)

Problem Statement: Showing the types of crimes and their frequency in the District of Columbia and providing the details of the crimes

Description: Police authorities are often called on to “put more feet on the street” to prevent crime and ensure order. However, due to limited resources, it is almost impossible to use them anytime, anywhere. In this project, you will work on the crime data, in the District of Columbia and analyze it using the Tableau tool. During visualization, you can use ‘crime categories’ and ‘days of the week’ as data types to see when and where crimes have occurred. In this project, you will also analyze the details of the crimes, such as, the area/location and the day of the week it has happened, etc. This project will help the local police get insightful information on where to put their crime prevention efforts on.

Highlights:

• A map should be plotted at the block site address level
• Shows the offense, the location, and the date of the crime
• Shows the frequency (in %) for each type of crimes
• Shows the crime details of every month by week/weekday/offense type (the dashboard should have various filters that will be applicable to all three sheets in the dashboard)
• An action from map should filter out the other two sheets, accordingly
• An action from the tree map and the bar chart should highlight the remaining two sheets according to the selection

Project 3: Analyzing Economic Data

Domain: Government

Problem Statement: How is unemployment affecting global malnutrition?

Description: In this Tableau project, you will be working on vast amounts of data and analyzing it to come up with trends, insights, and correlations. Datasets include the global unemployment figures for multiple years, world population statistics across several years, and the worldwide nutritional data. By analyzing this data, you will correlate the malnutrition problem with the unemployment rates using Tableau.

Highlights:

• Cleaning up Excel data and connecting with Tableau
• Using data blending and pivot tables
• Comparative analysis with the Tableau dashboard

Project 4: Analyzing Market Performance

Domain: Retail

Problem Statement: Using the Consumer Packaged Goods data to analyze which are the markets that are performing well for a particular retail enterprise using Tableau Desktop

Description: This Tableau Desktop project involves working with the complex Consumer Packaged Goods data to come up with the brand performance analysis, regions that are contributing good to the revenues, where there is a need to offer more discounts to spur sales, and making in-depth budget vs spend analysis for any particular year.

Highlights:

• Combining data sources, adding filters, and drilling down data
• Building an interactive dashboard and reports for detailed analysis
• Deriving real-time visualization of data for business insights