Improving Decisions with Predictive Analytics

This course is designed to shows how to effectively operationalize advanced analytics and data science in business processes. As organizations move beyond using analytics to monitor their business processes, they need new more advanced analytics and new techniques to apply them. This course focuses on defining and scoping the business problem for advanced analytics, ensuring that analytics are useful in business terms, and on operationalizing the results to use analytical decision-making to innovate business processes.

Using standards-based approaches (CRISP-DM, Decision Model and Notation-DMN) this course focuses on how to effectively apply data-driven decision-making and advanced analytics to business processes by identifying and modeling business decisions; applying advanced analytics and data science to improve these decisions; and using analytical improvements in decision-making to drive real process innovation.

Course Outline:

  • Introducing CRISP-DM, a methodology for advanced analytics and data science
  • Focusing on decision-making to maximize the ROI of analytics and data science
  • Decisions v processes and the role of data and analytics in both
  • Modeling decisions to build business understanding and bring clarity to requirements
  • Business-centric evaluation and deployment of analytics and data science
  • The role of analytics in decision-centric process improvement
  • Technical options for operationalizing analytics and data science in business processes
  • Continuous Improvement through ongoing decision monitoring and management
  • Decision-Centric Process Improvement

Unique Value of Course:

Participants will learn a proven approach to applying advanced analytics to improve business processes by focusing on the operational decisions within those processes.


  • Understand how a focus on decision-making ensures analytics and data science add value
  • Understand how analytics and data science can be used to improve decisions
  • Become familiar with the structure of CRISP-DM and its role in projects
  • Use decision modeling to understand business problems in a way that allows analytics and data science to be applied effectively
  • Compare and contrast processes and decisions and the different roles of data and analytics in each
  • Improve processes by improving decision-making

Who Should Attend:

  • Process improvement team members
  • Business analysts
  • Business and enterprise architects
  • Program and portfolio managers
  • Business strategists
  • Data scientists and other analytic professionals

Recommended Prior Courses:

Decision Management and Business Rules 101

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  1. Save $195 on your first eLearning course. Use discount code FIRSTCOURSE at checkout.
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