- Introduction to Tableau.
- Introduction to Business Intelligence.
- Prepare for Tableau Certification.
- Practical examples of each concept/feature of Tableau.
Tableau is a visual analytics platform transforming the way we use data to solve problems—empowering people and organizations to make the most of their data.
As the market-leading choice for modern business intelligence, the Tableau platform is known for taking any kind of data from almost any system, and turning it into actionable insights with speed and ease. It’s as simple as dragging and dropping. Plus, our industry-leading enablement resources, training, and global data community offer unparalleled support for our customers and their analytics investments. And on our mission to help people see and understand data, we go beyond our technology to ensure customer success by helping people build a data culture.
- Overview of Tableau and its features.
- Installation and setup.
- Connecting to data sources.
- Understanding Tableau interface.
- Creating basic charts (bar charts, line charts, pie charts, etc.).
- Sorting and filtering data.
- Formatting visualizations.
- Using colors, labels, and tooltips effectively.
- Working with maps and spatial data.
- Creating dual-axis and combination charts.
- Using sets, groups, and hierarchies.
- Implementing calculated fields and parameters.
- Understanding data types and roles in Tableau.
- Joins, blends, and relationships.
- Data aggregation and granularities.
- Pivot and split data for analysis.
- Building interactive dashboards.
- Design best practices and principles.
- Dashboard layout containers and objects.
- Dashboard actions and filters.
- Constructing compelling data narratives.
- Story points and annotations.
- Incorporating visualizations into a cohesive story.
- Engaging audience with data-driven insights.
- Data cleansing techniques.
- Handling missing values and outliers.
- Data reshaping and restructuring.
- Introduction to Tableau Prep for data preparation.
- Understanding Tableau calculations (aggregations, LOD expressions, table calculations).
- Forecasting and trend analysis.
- Statistical analysis and hypothesis testing.
- Integrating R and Python scripts for advanced analytics.
- Publishing to Tableau Server or Tableau Public.
- Embedding Tableau visualizations in web applications.
- Sharing workbooks and dashboards with colleagues.
- Access control and permissions management.
- Optimizing workbook performance.
- Data source optimization.
- Extracts vs. live connections.
- Tableau Server performance tuning.
