Data Analysis and Dashboard Design with Tableau

This course takes your Tableau skills to the next level by introducing advanced analytical techniques that enable deeper insights, smarter decision-making, and scalable dashboard design. You’ll begin by strengthening your foundation in calculations, learning how to create dynamic calculated fields, apply conditional logic, and define consistent business rules across analyses. This allows you to move beyond basic reporting and build logic-driven insights directly within Tableau. From there, the course explores time-based analytics, helping you analyze trends, compare performance across periods, and uncover patterns using techniques such as year-over-year analysis, running totals, and moving averages. These capabilities are essential for understanding how business performance evolves over time. The course then advances into Level of Detail (LOD) expressions and analytical visualization techniques. You’ll learn how to control data granularity, resolve aggregation challenges, and design sophisticated visualizations that reveal relationships, distributions, and outliers within complex datasets. Finally, you’ll focus on integrating advanced analytics into production-ready dashboards. This includes extending Tableau’s capabilities using tools like Python and TabPy, as well as designing high-performance dashboards that are scalable, interactive, and optimized for real-world deployment. By the end of this course, you will be able to: • Develop advanced calculated fields using functions, aggregations, and data types to support analytical workflows. • Apply conditional logic to model business rules and decision-making scenarios. • Analyze time-based data using comparative metrics, table calculations, and trend analysis. • Use LOD expressions to control granularity and improve analytical accuracy. • Build scalable, high-performance dashboards optimized for enterprise use. • Extend Tableau analytics using external tools such as Python and TabPy. Designed for learners who