Description

TDWI Predictive Analytics 2016 is a course that covers topics such as:

TDWI Predictive Analytics Fundamentals
- Common applications of predictive analytics
- Definitions, concepts, and terminology of predictive analytics
- To distinguish among various predictive model types and understand the purpose and statistical foundations of each
- How and where predictive analytics fits into a BI program and the relationships with business metrics, performance management, and data mining
- Organizational considerations for predictive analytics, including roles, responsibilities, and the need for business, technical, and management skills
TDWI Analytics Fundamentals
- An analytics topology to make sense of the variety of analytic types and techniques
- The concepts and practices of analytic modeling
- Analytic techniques for exploration, experimentation, and discovery
- The data side of analytics including data sourcing, data discovery, data cleansing, and data preparation
- The organizational side of analytics: self-service, central services, governance, etc
- The human side of analytics: communication, conversation, and collaboration
- A bit about emerging techniques and technologies shaping the future of analytics
TDWI Data Visualization Fundamentals
- Preparing data for visualization
- Visualization as a communication medium
- Choosing and using charts and graphs
- Components of visualization
- Visual design techniques
- Visual exploration and analysis
- Visual storytelling
- Extending visualization with infographics
- Data visualization tools