Foundations of Business Analytics: Prescriptive Analytics

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About Course

In this course, learners will explore the principles and methods of prescriptive analytics, a crucial aspect of business analytics that enables organizations to make optimal decisions. Through a combination of lectures, case studies, and practical exercises, students will learn how to apply advanced analytical techniques to recommend actions and solve complex business problems.

Disclaimer
This is a FRL program. You may be required to pay for optimized curriculum, student management and certificate. Learn more.

What Will You Learn?

  • Define prescriptive analytics and its role in business decision-making
  • Apply optimization techniques, such as linear and integer programming
  • Use simulation modeling to analyze complex systems and uncertainty
  • Implement decision analysis methods, including decision trees and sensitivity analysis
  • Evaluate and recommend solutions using multi-criteria decision-making techniques

Course Content

Course Content

  • Welcome
    01:48
  • What you should know
    01:07
  • A tale of two Companies
    05:17
  • Understanding prescriptive analytics
    07:40
  • Exploring the analytics taxonomy
    02:42
  • Looking at traditional data warehousing
    05:15
  • Exploring traditional business intelligence
    03:10
  • Understanding DWBI shortcomings
    04:28
  • Exploring big data
    07:38
  • Understanding the power of today’s advanced analytics
    03:58
  • Avoiding problems with big data and analytics
    05:50
  • Exploring the essential workflow for prescriptive analytics
    04:03
  • Collecting and processing data
    03:53
  • Beginning the workflow with event detection
    03:13
  • Categorizing events
    05:17
  • Processing and acting on events
    03:49
  • Looking at event processing examples
    02:56
  • Applying analytical models
    04:04
  • Differentiating different categories of hypotheses
    03:36
  • Building the business hypothesis clearinghouse
    03:47
  • Taking preliminary action on business hypotheses
    06:34
  • Comparing prescriptive, descriptive, and predictive analytics
    03:19
  • Understanding data correlation, analytics, and hypotheses
    03:54
  • Adding depth and breadth to enrich our analytics
    05:24
  • Managing high-velocity hypotheses
    02:17
  • Proving or disproving a business hypotheses
    08:25
  • Taking action based on a proven hypothesis
    10:14
  • Taking action based on a disproven hypothesis
    08:32
  • Taking action based on timer expiration
    03:57
  • Selling prescriptive analytics to your organization
    03:38
  • Using simple questions to sell prescriptive analytics
    06:19
  • Building the prescriptive analytics roadmap
    05:10
  • Training business users in prescriptive analytics
    07:06
  • Next steps
    01:48

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