What You Need to Know Before
You Start

Starts 8 June 2025 14:05

Ends 8 June 2025

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How to Use Tableau BI in 2025 - Step-by-Step Dashboard and Data Analysis Tutorial

Discover how to build dashboards, analyze data, and visualize insights with Tableau BI in this step-by-step tutorial for beginners.
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Overview

Discover how to build dashboards, analyze data, and visualize insights with Tableau BI in this step-by-step tutorial for beginners.

Syllabus

  • Introduction to Tableau BI
  • Overview of Tableau BI and its applications
    Installation and setup of Tableau software
    Understanding the Tableau interface
  • Connecting to Data Sources
  • Types of data sources supported by Tableau
    Connecting to local files and databases
    Data preparation and cleaning in Tableau
  • Building Your First Dashboard
  • Creating a new workbook
    Understanding dashboards and worksheets
    Basic dashboard layout and components
  • Visualizing Data
  • Types of visualizations in Tableau (bar charts, line charts, maps, etc.)
    How to choose the right visualization for your data
    Customizing visualizations (colors, labels, tooltips)
  • Advanced Visualization Techniques
  • Creating calculated fields
    Using filters and sorting data effectively
    Implementing parameters for dynamic dashboards
  • Data Analysis with Tableau
  • Basic statistical analysis and trends
    Time series analysis and forecasting
    Cohort analysis and segmentation
  • Interactivity and User Experience
  • Adding interactivity with actions (filters, highlights, and URL actions)
    Designing for user experience and accessibility
  • Sharing and Collaborating in Tableau
  • Publishing dashboards to Tableau Online or Tableau Server
    Collaborating with team members
    Exporting dashboards and reports
  • Best Practices and Tips
  • Dashboard performance optimization
    Avoiding common pitfalls in data visualization
    Keeping your Tableau skills up-to-date
  • Conclusion and Next Steps
  • Summary of key learnings
    Resources for further learning and practice
    Final Q&A and course feedback

Subjects

Data Science