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File List
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01.Welcome.108s.mp4 4.36 MB
02.What you should know.67s.mp4 2.52 MB
03.A tale of two companies.317s.mp4 13.18 MB
04.Understanding prescriptive analytics.459s.mp4 18.33 MB
05.Exploring the analytics taxonomy.162s.mp4 4.35 MB
06.Looking at traditional data warehousing.315s.mp4 12.08 MB
07.Exploring traditional business intelligence.190s.mp4 7.7 MB
08.Understanding DWBI shortcomings.268s.mp4 10.59 MB
09.Exploring big data.458s.mp4 12.21 MB
10.Understanding the power of today's advanced analytics.238s.mp4 9.47 MB
11.Avoiding problems with big data and analytics.350s.mp4 9.41 MB
12.Exploring the essential workflow for prescriptive analytics.243s.mp4 8.36 MB
13.Collecting and processing data.233s.mp4 9.06 MB
14.Beginning the workflow with event detection.193s.mp4 7.72 MB
15.Categorizing events.317s.mp4 12.53 MB
16.Processing and acting on events.229s.mp4 8.92 MB
17.Looking at event processing examples.176s.mp4 7.02 MB
18.Applying analytical models.244s.mp4 9.53 MB
19.Differentiating different categories of hypotheses.216s.mp4 8.59 MB
20.Building the business hypothesis clearinghouse.227s.mp4 6.17 MB
21.Taking preliminary action on business hypotheses.394s.mp4 11.11 MB
22.Comparing prescriptive, descriptive, and predictive analytics.199s.mp4 5.51 MB
23.Understanding data correlation, analytics, and hypotheses.234s.mp4 9.04 MB
24.Adding depth and breadth to enrich our analytics.324s.mp4 9.96 MB
25.Managing high-velocity hypotheses.137s.mp4 4.99 MB
26.Proving or disproving a business hypotheses.505s.mp4 13.95 MB
27.Taking action based on a proven hypothesis.614s.mp4 24.15 MB
28.Taking action based on a disproven hypothesis.512s.mp4 15.54 MB
29.Taking action based on timer expiration.237s.mp4 9.28 MB
30.Selling prescriptive analytics to your organization.218s.mp4 8.52 MB
31.Using simple questions to sell prescriptive analytics.379s.mp4 10.64 MB
32.Building the prescriptive analytics roadmap.310s.mp4 11.96 MB
33.Training business users in prescriptive analytics.426s.mp4 16.71 MB
34.Next steps.108s.mp4 3.98 MB
Info/01.Welcome.108s.info.json 6.39 KB
Info/02.What you should know.67s.info.json 6.55 KB
Info/03.A tale of two companies.317s.info.json 6.52 KB
Info/04.Understanding prescriptive analytics.459s.info.json 6.76 KB
Info/05.Exploring the analytics taxonomy.162s.info.json 6.61 KB
Info/06.Looking at traditional data warehousing.315s.info.json 6.63 KB
Info/07.Exploring traditional business intelligence.190s.info.json 6.29 KB
Info/08.Understanding DWBI shortcomings.268s.info.json 6.21 KB
Info/09.Exploring big data.458s.info.json 6.47 KB
Info/10.Understanding the power of today's advanced analytics.238s.info.json 6.69 KB
Info/11.Avoiding problems with big data and analytics.350s.info.json 6.71 KB
Info/12.Exploring the essential workflow for prescriptive analytics.243s.info.json 6.36 KB
Info/13.Collecting and processing data.233s.info.json 6.64 KB
Info/14.Beginning the workflow with event detection.193s.info.json 6.6 KB
Info/15.Categorizing events.317s.info.json 6.55 KB
Info/16.Processing and acting on events.229s.info.json 6.59 KB
Info/17.Looking at event processing examples.176s.info.json 6.56 KB
Info/18.Applying analytical models.244s.info.json 6.57 KB
Info/19.Differentiating different categories of hypotheses.216s.info.json 6.76 KB
Info/20.Building the business hypothesis clearinghouse.227s.info.json 6.7 KB
Info/21.Taking preliminary action on business hypotheses.394s.info.json 6.67 KB
Info/22.Comparing prescriptive, descriptive, and predictive analytics.199s.info.json 6.75 KB
Info/23.Understanding data correlation, analytics, and hypotheses.234s.info.json 6.83 KB
Info/24.Adding depth and breadth to enrich our analytics.324s.info.json 6.68 KB
Info/25.Managing high-velocity hypotheses.137s.info.json 6.68 KB
Info/26.Proving or disproving a business hypotheses.505s.info.json 6.76 KB
Info/27.Taking action based on a proven hypothesis.614s.info.json 6.66 KB
Info/28.Taking action based on a disproven hypothesis.512s.info.json 6.73 KB
Info/29.Taking action based on timer expiration.237s.info.json 6.63 KB
Info/30.Selling prescriptive analytics to your organization.218s.info.json 6.65 KB
Info/31.Using simple questions to sell prescriptive analytics.379s.info.json 6.27 KB
Info/32.Building the prescriptive analytics roadmap.310s.info.json 6.61 KB
Info/33.Training business users in prescriptive analytics.426s.info.json 6.63 KB
Info/34.Next steps.108s.info.json 6.37 KB
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