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Translating Data Into Business Intelligence with Sina Fak
Foundation
1.1 Intro (3:05)
1.2 Data Analytics vs. Business Intelligence (6:36)
1.3 7 Ways Combining Business Intelligence Insights And Experiments Will Exponentially Grow Your Business (15:15)
1.4 The Evolution of Business Intelligence Systems (10:12)
Insights
2.1 Extract Transform Load - The Data Infrastructure Required For Business Intelligence (5:55)
2.2 Evaluating what data you need to capture and how (9:00)
2.3 Mapping your customer buying journey (13:12)
2.4 Mapping your business ecosystem (13:26)
2.5 Data segmentation analysis (9:44)
2.6 Example of Insights from real customers (11:11)
2.7 Evaluating the quality of insights generated (4:23)
Ideation
3.1 The Scientific Method (3:05)
3.2 Setting objectives fo ideation (6:07)
3.3 Formulating your hypothesis (9:16)
3.4 Setting KPIs and learning objectives (7:09)
3.5 Prioritizing ideas (3:59)
3.6 Evaluating the quality of ideas generated (3:25)
Experimentation
4.1 Using experiments as a tool to translate data into intelligence (6:57)
4.2 Managing an experiment plan (PIE KPIs Hypothesis) (10:41)
4.3 Establishing an ongoing experiment process and culture (10:31)
4.4 Evaluating quality of experiments generated (2:55)
Analysis
5.1 Post test analysis (5:29)
5.2 Experiment Segmentation (7:09)
5.3 Reporting visualizing modeling data (12:24)
5.4 Communicating results across your team (3:50)
5.5 Conclusions (6:23)
5.6 Special Offer for INSIGHTS by ConversionAdvocates (0:44)
BI Live Class - Free Resource (50:24)
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4.4 Evaluating quality of experiments generated
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