Intermediate Tableau Course Overview

Intermediate Tableau Course Overview

The Intermediate Tableau course is designed to enhance learners' data visualization and analysis skills using Tableau, building on foundational knowledge to tackle more complex scenarios. It covers a range of topics from refreshing core concepts to connecting with various data sources, creating calculated fields, and employing advanced techniques like Level of Detail (LOD) expressions and table calculations. Learners will also become proficient in utilizing parameters, customizing maps, and creating dynamic dashboards for effective storytelling with data. By delving into data distribution analysis, trend analysis, and integrating external spatial files, participants gain a comprehensive understanding of data manipulation and presentation. This course empowers learners to design interactive dashboards, allowing end-users to explore data insights in a self-service manner, ultimately fostering data-driven decision-making within organizations.

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850

  • Live Online Training (Duration : 16 Hours)
  • Per Participant
  • Guaranteed-to-Run (GTR)
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♱ Excluding VAT/GST

Classroom Training price is on request

  • Live Online Training (Duration : 16 Hours)
  • Per Participant

♱ Excluding VAT/GST

Classroom Training price is on request

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Course Prerequisites

To ensure that you can fully benefit from our Intermediate Tableau course, we recommend that you have the following minimum prerequisites:


  • Basic understanding of data visualization concepts.
  • Familiarity with the fundamental operations of Tableau, such as creating basic charts and using the Tableau interface.
  • Experience in connecting Tableau to various data sources and performing basic data manipulations (e.g., sorting, filtering, and grouping data).
  • Ability to create simple calculated fields and understand basic functions in Tableau.
  • Knowledge of spreadsheet concepts, such as rows, columns, and basic functions in software like Microsoft Excel.
  • An analytical mindset and comfort with numbers and data analysis.

This foundational knowledge will help you to quickly grasp more advanced concepts and techniques taught in the Intermediate Tableau course.


Target Audience for Intermediate Tableau

The Intermediate Tableau course by Koenig Solutions caters to professionals looking to advance their data visualization and analytics skills.


  • Business Intelligence Professionals
  • Data Analysts
  • Reporting Analysts
  • Data Scientists
  • Data Visualization Analysts
  • Marketing Analysts
  • Financial Analysts
  • Operations Managers
  • IT Professionals who handle data
  • Project Managers who use data for decision-making
  • Consultants seeking to leverage Tableau for client insights
  • Academics and researchers utilizing data
  • Professionals in roles that require advanced reporting and data analysis skills


Learning Objectives - What you will Learn in this Intermediate Tableau?

Introduction to Learning Outcomes

In the Intermediate Tableau course, learners will deepen their data visualization skills, mastering advanced techniques for data analysis, dashboard creation, and storytelling with Tableau.

Learning Objectives and Outcomes

  • Gain proficiency in using Tableau's advanced features, including complex calculations, level of detail expressions, and dynamic parameters.
  • Develop expertise in connecting to various data sources and optimizing data for analysis by creating reusable connections, understanding join types, and blending data.
  • Learn to create and manipulate sets for defined data analysis, and apply advanced filtering techniques to refine results.
  • Master the art of crafting calculated fields and table calculations to perform sophisticated data operations.
  • Understand and implement table calculations, including setting scope and direction for comprehensive data insights.
  • Utilize parameters to create interactive and dynamic visualizations, enhancing user engagement and data exploration.
  • Acquire skills to create data snapshots through data extracts, optimizing performance and facilitating offline analysis.
  • Compare and measure progress effectively with advanced chart types like Bar-in-Bar and Bullet Graphs.
  • Customize maps and spatial analysis by integrating custom images, correcting geolocations, and using external files for geographic boundaries.
  • Analyze data distribution and trends using statistical tools such as Bins, Histograms, Trend Lines, and Forecasts, to make data-backed decisions.
  • Enhance dashboards and storytelling with data by applying best practices in design, user interactivity, and visual storytelling techniques.