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Course Outline
1. Introduction to Advanced Spotfire Analyst
- Course objectives and agenda.
- Review of Spotfire architecture.
- Differences between Spotfire Analyst and Spotfire Web Client.
- Best practices for advanced data analysis.
2. Spotfire Server and Environment Overview
- Components of the Spotfire platform.
- Connecting to Spotfire Server.
- Authentication and user roles.
- Managing preferences and user settings.
3. Navigating the Spotfire Web Client
- Working with the Web Player.
- Opening and sharing analyses.
- Using bookmarks and filters.
- Managing personal and shared content.
4. Managing Libraries and Information Assets
- Library structure and organization.
- Publishing analyses to the library.
- Version control and content management.
- Managing permissions and access rights.
5. Collaboration and Secure Content Sharing
- Sharing analyses with teams.
- Configuring user roles and access controls.
- Managing collaborative workflows.
- Best practices for secure data sharing.
6. Creating Information Links and Accessing Enterprise Data
- Information Designer concepts.
- Creating Information Links.
- Connecting to relational databases.
- Working with multiple data sources.
- Optimizing data retrieval performance.
7. Advanced Data Preparation
- Transforming and cleaning data.
- Data wrangling techniques.
- Managing calculated columns.
- Pivoting and unpivoting datasets.
- Combining and joining multiple data tables.
8. Advanced Visualizations
- Creating advanced charts and dashboards.
- Map charts and geographic analysis.
- Scatter plots, box plots, and heat maps.
- Hierarchical visualizations.
- Interactive filtering and drill-down analysis.
- Visualization design best practices.
9. Advanced Analysis Using Expressions
- Calculated values and custom expressions.
- OVER functions.
- Nested expressions.
- Custom calculations.
- Dynamic measures.
- Performance optimization for expressions.
10. Creating Interactive Dashboards
- Property Controls.
- Input controls and parameters.
- Dynamic filtering.
- Document properties.
- User-driven dashboard interactions.
11. Integrating Statistical Engines
- Introduction to data functions.
- Integrating R with Spotfire.
- Executing R scripts.
- Using TERR for statistical analysis.
- Automating statistical workflows.
12. Data Relationships and Predictive Analytics
- Understanding relationships between datasets.
- Correlation and regression analysis.
- Predictive modeling concepts.
- Building predictive workflows.
- Evaluating model performance.
13. Multivariate Data Analysis
- Exploring multidimensional datasets.
- Clustering techniques.
- Principal Component Analysis (PCA).
- Pattern identification.
- Outlier detection.
14. Performance Optimization and Troubleshooting
- Improving dashboard performance.
- Optimizing data loading.
- Managing large datasets.
- Troubleshooting common Spotfire issues.
- Best practices for maintaining analyses.
15. Best Practices and Real-World Applications
- Dashboard design guidelines.
- Common implementation scenarios.
- Governance and security recommendations.
- Case studies and practical examples.
16. Summary and Hands-on Workshop
- Review of key concepts.
- End-to-end practical exercise.
- Questions and answers.
- Additional learning resources and next steps.
Requirements
- Prior experience with Spotfire is required.
Audience
- Business analysts.
14 Hours
Testimonials (2)
Professional and very practical, usuefull in a daily work
Jozefin Rekasi - SC Automobile Dacia SA
Course - Advanced Data Analysis with TIBCO Spotfire
I liked Pablo's style, the fact that he covered a lot of subjects from report design , customization with html to implementing simple ML algortithms. Good balance theoretical information / exercices. Pablo really covered all topics i was interested in and gave comprehensive answers to my questions.
