1. Data @ the core of Enterprise Agile Mathew Aniyan Program Manager, Microsoft

2. Abstract Agile adopts an empirical approach to software development. One of the key aspects of a successful Agile Implementation is how quickly we can react to change. For this, we need to ensure that data flows seamlessly from customer to the Agile team. This data should form a critical part of our decision making. Is the customer successful in using our product or service? Which features are customer most interested in? Where are the friction points in usage? Where are the failures happening in our product? How is the customer engaging with our product over time? and many more similar questions. In this talk, I discuss best practices in data collection, analysis and visualization and how data can make your Agile process and thereby your business more effective.

3. Agile Manifesto - http://www.agilemanifesto.org/

4. Principles behind the Agile Manifesto Welcome changing requirements, even late in development. Agile processes harness change for the customer's competitive advantage. At regular intervals, the team reflects on how to become more effective, then tunes and adjusts its behavior accordingly.

5. Data as the lifeblood of Agile Helps understand changing requirements Measures progress against goals

6. Before we start: Privacy Classify your data Seek customer permission Security Who can access? How to secure? Err on the side of caution

7. Design your data

8. Start with the Business Questions

9. How will you visualize the data?

10. What decision will you make?

11. A Sample Business Question Demo

12. Data Collection Infrastructure

13. Hot Path Demo

14. Warm Path Demo

15. Cold Path Demo

16. Surveys A sample questionnaire

17. Analysis – Per Incident Root Cause Analysis 5 Whys

18. Analysis – Per Day Daily trends Operational

19. Analysis – Per Week Operational Learning focused

20. Mean Time To Detect To Fix Between Failures

21. Analysis – Per Month Business focused Experiments

22. Machine Learning K-Means clustering

23. Visualization Samples

24. Availability

25. Usage Funnels

26. Map Visualizations

27. Cohorts

28. Flow Diagrams

29. TreeMap

30. Animated Bubble Charts Demo

31. Tables with Sparklines

32. Summary Use data to drive your decisions Plan your data Develop the right data collection infrastructure Analyze at needed Use visualizations to communicate with data effectively