Extend your analytics program from gaining insight to providing foresight with this great introduction to predictive analytics skills.
Predictive analytics is a set of techniques used to gain new knowledge from large amounts of raw data by combining data mining, statistics, and modeling. Predictive analytics goes beyond insight (knowing why things happen) to foresight (knowing what is likely to happen in the future). Predictive models use patterns in historical data to identify and quantify probabilities of future opportunities and risks. Virtually every industry—insurance, telecommunications, financial services, retail, healthcare, pharmaceuticals, and many more—uses predictive analytics for applications such as marketing, customer relationship management, fraud detection, collections, cross-sell and up-sell, and risk management. This course introduces predictive analytics skills, which encompass a variety of statistical modeling techniques, including linear and logistic regression, time-series analysis, classification and decision trees, and machine-learning techniques. Beyond statistics skills, predictive analytics requires knowledge of problem framing, data profiling, data preparation, and model evaluation.
You Will Learn
- Definitions, concepts, and terminology of predictive analytics
- Common applications of predictive analytics
- How and where predictive analytics fits into a BI program and the relationships with business metrics, performance management, and data mining
- To distinguish among various predictive model types and understand the purpose and statistical foundations of each
- Organizational considerations for predictive analytics, including roles, responsibilities, and the need for business, technical, and management skills
BI program managers, architects, and project managers; business analysts who want to extend from gaining insight to providing foresight; business managers who need new tools to help them shape the future of the business; anyone interested in the basics of predictive analytics.
Continuing Professional Education Credits: 5
Apply these credits toward your CBIP recertification. Not certified? Learn more about CBIP and how to get certified https://tdwi.org/pages/education/cbip-certification/cbip-home.aspx here.
BI Consultant and Instructor, CBIP
Mark Peco, CBIP, is an experienced consultant, educator, manager, analyst, and team builder. He holds a graduate degree in engineering from the University of Waterloo and has led numerous consulting and software development projects helping clients to adapt to fundamental shifts in business models and requirements. His experience includes strategy development, business intelligence, data warehousing, compliance, analytics, mathematical modeling, and application development. Mark’s industry experience includes the energy, metals, and financial sectors.