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Tableau Desktop Fundamentals (TTDTABDF2)

The Tableau Desktop Fundamentals (TTDTABDF2) is an intermediate-level 2 Days Training Program designed for IT Enthusiasts striving to learn the key features & functionalities of Tableau.


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Learning Style



2 Days

Course Duration

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The Tableau Desktop Fundamentals (TTDTABDF2) is an intermediate-level 2 Days Training Program designed for IT Enthusiasts striving to learn the key features & functionalities of Tableau.

Course Information

About this Course:

The Tableau Desktop Fundamentals (TTDTABDF2) is an intermediate-level 2 Days Training Program designed for IT Enthusiasts striving to learn the key features & functionalities of Tableau. This course provides a comprehensive overview of Tableau Data Visualization Features and helps professionals nurture the skills required to proficiently create Simple & Advanced Visualizations and understand the basic of integrating visualizations with interactive dashboards. On average, a professional Tableau Developer earns $104,672 annually.

This is an independent training program and is customized and adjusted as per the learners’ unique requirements. This course encompasses flexible learning material and is instructed by a Seasoned Tableau Expert who knows the ins and outs of Tableau Visualization Capabilities. This course presents a perfect learning opportunity for professionals striving to develop conceptual understanding of Tableau Entry-Level concepts and build the foundation required to attain more advanced courses. 

Course Objectives:

The core objective of this course is to help professionals develop a better understanding and sound knowledge of the following key concepts:

  • Connecting, Saving, and Editing Data Source in Tableau
  • Understanding Basic Terminologies of Tableau
  • Development of Powerful Visualizations using Paradigm or Tableau Interface
  • Creation of Basic Calculations such as Arithmetic, Ratios, & Logic Statements
  • String Manipulation, Date Math, Quick Table, & Custom Aggregation Calculations
  • Data Representation through Cross Tabs, Box Plots, Highlight Tables, & Scatter Plots
  • Data Representation through Maps such as Heat Maps, TreeMaps, & Geographic Maps
  • Data Representation through Distribution Charts, Pie Charts, & Bar Charts
  • Highlighting Data Elements using Reference Lines and Sharing Visualizations
  • Creating Effective Visualizations using Bins, Sorts, Groups, Sets, Filters, & Hierarchies
  • Data Sources Change Management and Deletion, Field Addition, & Name Modification
  • Creating Multiple Dimension Visualization with Measure Value & Measure Name


  • Candidates interested in Learning Fundamentals and Essentials of Tableau
  • Professionals interested in Learning New & Improved Features of Tableau
  • Candidates striving to pursue Professional Career in Tableau Server Administration
  • Professionals interested in Gaining Basic Understanding of Tableau


Professionals planning to enroll in the Tableau Desktop Fundamentals (TTDTABDF2) course must have experience of working in Data Fields either Analytical or Technical.

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More Information

More Information
Subjects Data Platform
Lab Access No
Technology Tableau
Learning Style Virtual Classroom
Learning Type Course
Difficulty Beginner
Course Duration 2 Days
Language English

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Course Expert:


Tom Robertson
(Data Science Enthusiast)

Tom is an innovator first, and then a Data Scientist & Software Architect. He has integrated expertise in business, product, technology and management. Tom has been involved in creating category defining new products in AI and big data for different industries, which generated more than hundred million revenue cumulatively, and served more than 10 million users.
As a Data Scientist and Software Architect Tom has extensive experience in data science, engineering, architecture and software development. To date Tom has accumulated over a decade of experience in R, Python & Linux Shell programming.

Tom has expertise on Python, SQL, and Spark. He has worked on several libraries including but not limited to Scikit-learn, Pandas, NumPy, Matplotlib, Seaborn, SciPy, NLTK, Keras, and Tensorflow.

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