15 Topics
10 Days
Programme Overview
Training Description
Who Should Attend
This course is ideal for;
- Data Analysts
- Business Intelligence Professionals
- Data Scientists
- Reporting Specialists
- Dashboard Developers
- Data Visualization Specialists
- Anyone needing advanced visualization skills
Session Objectives
- Understand the fundamentals of advanced data visualization with Tableau/Power BI.
- Master the creation of interactive dashboards for Big Data.
- Utilize advanced charting techniques for complex data representation.
- Optimize dashboard performance for large datasets.
- Implement data storytelling and narrative techniques.
- Integrate advanced data analysis features into dashboards.
- Design user-friendly and intuitive dashboards.
- Troubleshoot and debug visualization issues.
- Implement data security and access control in visualizations.
- Integrate Tableau/Power BI with various data sources.
- Understand how to monitor and maintain dashboards.
- Explore advanced visualization patterns and techniques.
- Apply real world use cases for advanced data visualization.
About the Course
Transform raw data into compelling stories with our Advanced Data Visualization with Tableau/Power BI Training Course. This program is designed to equip you with the advanced skills to create interactive dashboards and visualizations for Big Data, enabling you to extract and communicate meaningful insights effectively. In today's data-driven landscape, the ability to visualize complex datasets is crucial for driving informed decisions. Our data visualization training course provides hands-on experience and expert guidance, empowering you to build impactful and intuitive dashboards.
This Tableau/Power BI training delves into the core concepts of advanced data visualization, covering topics such as interactive dashboard design, advanced charting techniques, and performance optimization. You'll gain expertise in using industry-leading tools to build interactive dashboards and visualizations for Big Data that meet the demands of modern data analysis. Whether you're a data analyst, business intelligence professional, or data scientist, this advanced data visualization course will empower you to communicate data insights effectively.
Curriculum & Topics
15 Topics | 10 Days
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Subtopic 1.1:
Fundamentals of advanced data visualization.
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Subtopic 1.2:
Overview of Tableau and Power BI capabilities.
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Subtopic 1.3:
Setting up a visualization development environment.
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Subtopic 1.4:
Introduction to advanced visualization concepts.
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Subtopic 1.5:
Best practices for advanced visualization.
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Subtopic 2.1:
Designing interactive dashboards for Big Data.
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Subtopic 2.2:
Implementing drill-down and filter functionalities.
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Subtopic 2.3:
Utilizing action filters and parameters.
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Subtopic 2.4:
Creating dynamic and responsive dashboards.
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Subtopic 2.5:
Best practices for dashboard design.
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Subtopic 3.1:
Implementing advanced chart types (treemaps, sankey charts).
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Subtopic 3.2:
Utilizing custom calculations and aggregations.
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Subtopic 3.3:
Creating geospatial visualizations and maps.
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Subtopic 3.4:
Implementing advanced time series analysis.
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Subtopic 3.5:
Best practices for advanced charting.
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Subtopic 4.1:
Optimizing dashboard performance for large datasets.
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Subtopic 4.2:
Utilizing data extracts and aggregations.
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Subtopic 4.3:
Implementing query optimization techniques.
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Subtopic 4.4:
Utilizing performance recording and analysis.
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Subtopic 4.5:
Best practices for performance optimization.
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Subtopic 5.1:
Implementing data storytelling principles.
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Subtopic 5.2:
Utilizing narrative techniques for effective communication.
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Subtopic 5.3:
Creating guided analytics and interactive presentations.
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Subtopic 5.4:
Designing dashboards for specific audiences.
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Subtopic 5.5:
Best practices for data storytelling.
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Subtopic 6.1:
Implementing advanced calculations and table calculations.
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Subtopic 6.2:
Utilizing predictive analytics and forecasting.
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Subtopic 6.3:
Implementing statistical analysis in visualizations.
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Subtopic 6.4:
Creating interactive reports and summaries.
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Subtopic 6.5:
Best practices for data analysis.
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Subtopic 7.1:
Designing intuitive and user-friendly dashboards.
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Subtopic 7.2:
Implementing accessibility and usability guidelines.
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Subtopic 7.3:
Creating consistent and visually appealing dashboards.
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Subtopic 7.4:
Utilizing design principles for effective communication.
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Subtopic 7.5:
Best practices for user-friendly design.
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Subtopic 8.1:
Debugging visualization issues and errors.
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Subtopic 8.2:
Analyzing performance and data issues.
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Subtopic 8.3:
Utilizing debugging tools and techniques.
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Subtopic 8.4:
Resolving common visualization problems.
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Subtopic 8.5:
Best practices for troubleshooting.
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Subtopic 9.1:
Implementing data security in visualizations.
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Subtopic 9.2:
Utilizing user authentication and authorization.
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Subtopic 9.3:
Implementing data access control and row-level security.
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Subtopic 9.4:
Managing data permissions and privileges.
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Subtopic 9.5:
Best practices for security.
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Subtopic 10.1:
Integrating Tableau/Power BI with various data sources.
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Subtopic 10.2:
Utilizing data connectors and APIs.
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Subtopic 10.3:
Implementing data blending and relationships.
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Subtopic 10.4:
Managing data connections and data sources.
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Subtopic 10.5:
Best practices for data integration.
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Subtopic 11.1:
Monitoring dashboard performance and usage.
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Subtopic 11.2:
Implementing dashboard maintenance strategies.
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Subtopic 11.3:
Utilizing monitoring tools and techniques.
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Subtopic 11.4:
Managing dashboard updates and changes.
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Subtopic 11.5:
Best practices for monitoring.
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Subtopic 12.1:
Implementing advanced visualization patterns (small multiples, parallel coordinates).
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Subtopic 12.2:
Utilizing custom visualizations and extensions.
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Subtopic 12.3:
Implementing interactive data exploration tools.
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Subtopic 12.4:
Advanced techniques for data representation.
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Subtopic 12.5:
Best practices for advanced patterns.
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Subtopic 13.1:
Deploying visualizations on cloud platforms.
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Subtopic 13.2:
Utilizing cloud-based visualization services.
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Subtopic 13.3:
Optimizing cloud resources for visualizations.
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Subtopic 13.4:
Best practices for cloud deployment.
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Subtopic 14.1:
Implementing data governance policies in visualizations.
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Subtopic 14.2:
Utilizing metadata management tools.
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Subtopic 14.3:
Implementing data lineage and data dictionary.
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Subtopic 14.4:
Best practices for data governance.
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Subtopic 15.1:
Emerging trends in data visualization.
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Subtopic 15.2:
Utilizing AI and automation in visualizations.
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Subtopic 15.3:
Implementing immersive and interactive visualizations.
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Subtopic 15.4:
Best practices for future visualizations.
