Introduction
Overview of TIBCO Statistica Features
- Interactive UI and workflow UI
- Analytic facilities and unique features
- Statistica Help
Getting Started with TIBCO Statistica
- Installation
- MS Office integration
- Selecting a data file
- Templates
Exploring Data Analysis Capabilities
- Commonly used statistical tests
- Elementary concepts (variables, measurement scales, relations, etc.)
- Statistical Advisor feature
Exploring Statistics Basics
- Correlations and ANOVA
- Variable bundles
- By-group analyses
- Summary results panels
Managing Data Using TIBCO Statistica
- Spreadsheet formulas
- Workspace nodes
- Managing output
- Printing, importing, and exporting
Managing Statistica Settings and Projects
- Project actions
- Customizing settings (toolbar, menus, commands)
Working with Spreadsheets, Reports, and Macros
- Using spreadsheets and workbooks
- Creating graphs and reports
- Working with macros
Exploring Advanced Analytics Topics
- Statistica Data Miner (SDM)
- Machine learning
- Engineering applications
- Design of Experiments (DOE)
Summary and Conclusion
Introduction
Review of Basic Features and Architecture of Splunk
Developing a Splunk Application and a Technology Add-on
Connecting Data to Splunk
- Understanding various data input methods and sources
- Processing data
- Improving the input process
Conducting Advanced Data Analytics
- Manipulating and filtering data
- Combining searches and using subsearches
- Working with time and multivalue fields
- Creating advanced reports
- Using geography and location
- Using advanced transactions
- Dealing with anomalies
- Predicting and trending
- Understanding machine learning
Performing Advanced Visualization
- Drilldown
- Sunburst Sequence
- Geospatial visualization
- Punchcard visualization
- Calendar heatmap visualization
- Sankey diagram
Customizing Dashboard
- Using Dashboard controls
- Managing multi-search
- Customizing tokens
- Customizing layout, look and feel
- Implementing the custom alert action
Integrating Splunk with Other Enterprise Systems
- Working with the Splunk SDK
- Splunk with Python and R for analytics
- Splunk with Tableau for visualization
Troubleshooting
Summary and Conclusion
Introduction
Core Programming and Syntax in R
- Variables
- Loops
- Conditional statements
Fundamentals of R
- What are vectors?
- Functions and packages in R
Preparing the Development Environment
- Installing and configuring R and RStudio
- Setting up Rserve
Classifying Data
- Moving data between R and Tableau
- Preparing and cleaning data
- Modeling and scripting in R
Regressions in R and Tableau
- Creating a regression model
- Visualizing regressions
- Predicting and comparing values
Clustering and Models
- Working with clustering algorithms
- Creating clusters
- Visualizing clustered data
Advanced Analytics with R and Tableau
- Using CRISP-DM
- Working with TDSP models
- Summarizing data
