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
