Advanced Data Analytics

Categories: Data Analytics
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About Course

Advanced Visualization with Tableau

Once you’ve built a solid foundation with the Basics and Intermediate Tableau Desktop courses, the next step is to master advanced techniques that transform your dashboards into powerful, scalable, and interactive analytics solutions.

This course is designed for learners who are ready to push Tableau to its limits—going beyond standard charts and filters to advanced calculations, custom visualizations, performance tuning, and integration with other tools like R and Python.

What You’ll Learn

  • Advanced Calculations – LOD expressions, nested calculations, and table calculations for complex analysis.

  • Parameters Mastery – Build highly interactive dashboards with parameter-driven controls.

  • Advanced Mapping Techniques – Custom geocoding, spatial joins, polygon maps, and background images.

  • Dashboard Design Best Practices – Optimize layouts, improve user experience, and apply storytelling principles.

  • Data Blending & Joins – Integrate multiple data sources and perform advanced joins for unified analysis.

  • Performance Optimization – Improve workbook speed with extracts, source filters, and Tableau’s performance tools.

  • Advanced Visualizations – Create tree maps, heat maps, box plots, bullet charts, and custom visuals.

  • Integration with R & Python – Enhance Tableau with predictive models and advanced statistical methods.

  • Custom SQL Queries – Write SQL directly in Tableau for more control and efficiency.

  • Advanced Interactivity – Add parameter actions, set actions, URL actions, and advanced dashboard interactions.

  • Tableau Extensions – Extend Tableau’s functionality with custom add-ons and external integrations.

  • Security & Permissions – Apply row-level and column-level security, encryption, and access controls.

Why Take This Course?

✅ Mastery-Level Tableau Skills – Go beyond intermediate techniques to create sophisticated, business-ready dashboards.
✅ Real-World Problem Solving – Learn how to handle complex datasets, optimize performance, and support enterprise-level analytics.
✅ Cutting-Edge Visualizations – Build dashboards that stand out with advanced visual types and custom features.
✅ Analytics + Programming – Integrate R/Python for predictive analytics and machine learning.
✅ Enterprise Readiness – Gain expertise in security, permissions, and data governance.
✅ Career Impact – Advanced Tableau Desktop skills are highly valued across industries, helping you stand out in roles like Data Analyst, BI Developer, and Analytics Consultant.

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What Will You Learn?

  • Advanced Calculations: Utilize Tableau's calculation features to perform complex calculations, including level of detail (LOD) expressions, table calculations, and nested calculations.
  • Parameters: Master the use of parameters to allow users to interactively control aspects of the visualization, such as filtering data, changing measures, or altering visual properties.
  • Advanced Mapping Techniques: Explore advanced mapping techniques such as custom geocoding, background images, polygon maps, and integration with spatial files or APIs.
  • Dashboard Design Best Practices: Learn about best practices for designing effective dashboards, including layout optimization, interactivity, user experience considerations, and storytelling.
  • Data Blending and Joins: Understand how to blend data from multiple sources and perform advanced join operations to integrate disparate datasets for analysis.
  • Performance Optimization: Optimize the performance of your Tableau workbooks by managing data extracts, minimizing calculations, utilizing data source filters, and leveraging performance recording tools.
  • Advanced Visualizations: Experiment with advanced visualization types such as tree maps, heat maps, box plots, bullet graphs, and custom visualizations using extensions or JavaScript integration.
  • Integration with R or Python: Incorporate advanced analytics and machine learning models into Tableau using R or Python integration to perform predictive analytics or advanced statistical analysis.
  • Custom SQL Queries: Learn how to write and optimize custom SQL queries within Tableau to directly access data and perform advanced data manipulation.
  • Advanced Interactivity: Explore advanced interactivity features such as parameter actions, set actions, dashboard actions, and URL actions to create dynamic and interactive visualizations.
  • Tableau Extensions: Experiment with Tableau extensions to extend the capabilities of Tableau, integrating with external services, embedding web content, or creating custom functionality.
  • Security and Permissions: Understand advanced security features in Tableau, including row-level security, column-level security, and data encryption to ensure data protection and compliance.

Course Content

Data Fetch techniques

  • Intro to custom SQL queries
    00:00
  • Custom SQL queries examples
    00:00

SQL basics

Advanced SQL

Advanced Calculations

Parameters

Tableau Order of Operations

Time Related Data Analysis
Temporal data is prevalent in various fields and applications, including: Financial Analysis: Stock market data, trading volumes, and economic indicators are often analyzed over time to identify trends, patterns, and correlations. Sensor Data: IoT (Internet of Things) devices generate temporal data such as temperature readings, humidity levels, and motion detection, which can be analyzed to monitor trends or detect anomalies. Healthcare: Patient records, vital signs, medication schedules, and medical events are temporal data points used for tracking patient health over time and assessing treatment effectiveness. Climate and Environmental Monitoring: Weather data, climate patterns, pollution levels, and natural disaster occurrences are examples of temporal data used for forecasting and studying long-term trends. Project Management: Gantt charts, project timelines, task durations, and milestones represent temporal data used for scheduling, resource allocation, and progress tracking in project management. Social Media and Web Analytics: Timestamps on posts, website visits, user interactions, and engagement metrics provide temporal insights into user behavior, content popularity, and marketing campaign effectiveness.

Extensions

Analytics extensions

Advanced Python

Geo spatial Analysis

Dashboard objects and Interactivity

Dashboards best practices and Stories

Security and privacy

Dashboard Performance

Quiz

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