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Prescriptive analytics enables managers to explore different scenarios and evaluate new business opportunities by playing the “what-if” game. It enables the evaluation and comparison of different options as part of the decision making process. This leads to a deeper understanding about how to define and achieve business and operating goals.
Implementing prescriptive analytics using simulation methods within a Business Intelligence (BI) program provides additional capabilities to existing BI programs. Answers to advanced business questions starting with "why" and "what if" can now be answered. Maintaining the models in a calibrated and reliable manner over time requires rigorous data management practices based on principles of integration and quality.
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Prescriptive analytics using simulation extends and enhances the capabilities of BI programs and BI programs enable the utility and maintainability of the necessary data and models.
This 4-hour online training course provides an introduction to prescriptive analytics using simulation models applied to areas that are relevant to business analysts, operations planners, decision makers, functional managers and BI team members. The basic concepts are introduced and a framework is provided that positions simulation analytics within a broader BI Program. Categories of models are described that provides an overview of the breadth of potential opportunities for prescriptive analytics within diverse organizations.
You will learn:
- Basic capabilities of simulation
- Categories of models and modeling techniques
- Domains of applicability
- How to build and implement simulation models
- Data management requirements for simulation
- How business problems can be defined and solved
- The role of experimental design
- How insights can be generated
- How to explore and discover possible routes to successful outcomes
- How business intelligence, analytics, and simulation are related disciplines
This course is geared towards:
- BI program leaders
- BI architects and project managers
- Business analytics team members
- Business managers and decision makers
- Functional analysts
- Operations managers
- Process improvement specialists
BA-02 Prescriptive Analytics Using Simulation Models
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BA-02-00 About the Course (8 min)
BA-02-01 Introduction (54 min)
- Basic Concepts
- Capabilities of Simulation
- Business intelligence Framework
- Simulation Framework
BA-02-02 Principles and Practices (38 mins)
- Context and Opportunities
- Application Areas
- Systems Models
- Model Components
- System Simulation
BA-02-03a Modeling Techniques - Part I (60 mins)
- Overview
- Continuous Physical Models
- Business Process Models
- Stock and Flow Models
BA-02-03b Modeling Techniques - Part II (43 mins)
- Monte Carlo Models
- Discrete Event Models
- Empirical Models
BA-02-04 Simulation (49 mins)
- Opportunities and Techniques
- Data Management Considerations
- Simulation and the BI Program
- Case Study
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Click –here- to download a more detailed outline of this course.
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This exam tests knowledge and understanding of basic concepts, principles, and terminology of prescriptive analytics.
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You will be tested in these areas:
- Simulation capabilities
- Components, roles and organization for simulation analytics
- Opportunities and applications for simulation analytics
- System models including business process and stock and flow modeling
- Simulation models including Monte Carlo, Discrete Event, and Empirical Modeling
- Business applications of simulation
- Data management for simulation
- Simulation and business intelligence
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Additional Information
Number of Questions: 20
Time Limit: 40 Minutes
Passing Score: 70%
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Once you pass the exam, you will receive a Certificate of Education
documenting that you have demonstrated mastery of the topic. Course
exams count towards eLC certification programs. Visit our Certification page for more information about our various programs.
We recommend that you take detailed notes and review the course material multiple times before taking this exam.
Click here to learn more about CIMP exams.
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Course Review 
