Description

Introduction of Advanced Tableau for data analytics:

As businesses increasingly rely on data to drive decisions, mastering advanced data analytics and visualizations becomes essential for gaining deeper insights. This course, “Advanced Tableau: Mastering Data Analytics and Visualizations,” is designed for those who are already familiar with Tableau’s basics and are looking to take their skills to the next level. In this training, you will delve into advanced features of Tableau, including complex calculations, custom visualizations, data blending, and Tableau Server integration. By the end of this course, you’ll be equipped to create sophisticated, interactive dashboards and extract actionable insights from your data.

Prerequisites:

• Completion of a beginner-level Tableau course or equivalent experience
• Solid understanding of Tableau basics, including data connections, basic charts, and dashboards
• Familiarity with data concepts such as joins, calculations, and aggregations

Table of Contents:

1: Advanced Data Connections and Preparation

1.1 Connecting to Advanced Data Sources
1.1.1 Connecting to cloud databases and APIs
1.1.2 Working with big data sources like Hadoop and Google BigQuery

1.2 Advanced Data Preparation Techniques
1.2.1 Complex joins and unions
1.2.2 Data pivoting and unpivoting
1.2.3 Handling null values and data anomalies

1.3 Using Tableau Prep for Data Cleaning
1.3.1 Introduction to Tableau Prep Builder
1.3.2 Data flows and transformations
1.3.3 Combining and shaping data for analysis

2: Complex Calculations and Table Calculations

2.1 Advanced Calculated Fields
2.1.1 Nested calculations and logical functions
2.1.2 Date calculations and date functions
2.1.3 Level of Detail (LOD) expressions like FIXED, INCLUDE, and EXCLUDE

2.2 Table Calculations
2.2.1 Understanding table calculations and their scope
2.2.2 Running totals, moving averages, and percentages
2.2.3 Custom table calculations and addressing

2.3 Using Calculations for Advanced Analytics
2.3.1 Creating cohort analysis
2.3.2 Pareto charts and waterfall charts
2.3.3 Predictive analytics using trend lines and forecasting

3: Advanced Visualizations and Techniques

3.1 Creating Custom Visualizations
3.1.1 Parameterized charts like dynamic top N and what-if analysis
3.1.2 Using dual-axis and blended axes for combined charts
3.1.3 Heat maps, tree maps, and bullet charts

3.2 Designing for User Interaction
3.2.1 Using parameters for interactive dashboards
3.2.2 Customizing tooltips and incorporating visual elements
3.2.3 Advanced actions including URL actions, set actions, and parameter actions

3.3 Building Complex Dashboards
3.3.1 Dashboard layout strategies for large data sets
3.3.2 Adding advanced interactivity with user controls
3.3.3 Optimizing performance for large data and complex visualizations

4: Data Blending and Advanced Joins

4.1 Understanding Data Blending
4.1.1 Differences between data blending and joins
4.1.2 Using primary and secondary data sources
4.1.3 Troubleshooting data blending issues

4.2 Advanced Joins
4.2.1 Cross-database joins
4.2.2 Using calculated joins for dynamic relationships
4.2.3 Dealing with many-to-many relationships

4.3 Combining Data from Multiple Sources
4.3.1 Blending data for complex dashboards
4.3.2 Combining internal and external data for comprehensive analysis
4.3.3 Data blending vs. cross-database joins: Best practices

5: Tableau Server and Tableau Online Integration

5.1 Introduction to Tableau Server and Tableau Online
5.1.1 Differences between Tableau Server and Tableau Online
5.1.2 Tableau Server architecture and components
5.1.3 Publishing workbooks to Tableau Server(Ref: Tableau Desktop Specialist Certification Training)

5.2 Advanced Collaboration with Tableau Server
5.2.1 Managing permissions and security
5.2.2 Creating and managing data sources on Tableau Server
5.2.3 Scheduling data refreshes and alerts

5.3 Performance Tuning and Optimization
5.3.1 Improving dashboard performance
5.3.2 Managing server resources and usage
5.3.3 Troubleshooting performance issues

6: Real-Time Data Analytics and Custom Scripts

6.1 Connecting to Real-Time Data Sources
6.1.1 Working with streaming data and live connections
6.1.2 Real-time data visualization strategies
6.1.3 Integrating Tableau with live data feeds

6.2 Using R and Python Scripts in Tableau
6.2.1 Introduction to R and Python integration
6.2.2 Running advanced analytics scripts in Tableau
6.2.3 Using scripts for predictive modeling and statistical analysis

6.3 Advanced Analytics Techniques
6.3.1 Clustering and segmentation
6.3.2 Time-series analysis
6.3.3 Anomaly detection and outlier analysis

7: Capstone Project and Review

7.1 Capstone Project Overview
7.1.1 Project guidelines and expectations
7.1.2 Selecting a complex dataset
7.1.3 Designing and building a comprehensive, interactive dashboard

7.2 Review and Q&A
7.2.1 Recap of advanced topics
7.2.2 Open Q&A session for participants

7.3 Project Presentations
7.3.1 Participants present their capstone projects
7.3.2 Group feedback and discussion

This course is structured to build on existing Tableau knowledge, gradually introducing more complex techniques and tools. The capstone project provides an opportunity to apply advanced skills to a real-world scenario, ensuring participants can implement what they’ve learned effectively.

Reference