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The What, Why and How of Analytics Testing

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Here are slides from my talk on "What, Why and How of Analytics Testing" at Selenium Conference, Berlin 2017.

This talk focusses on Analytics related to Browser & Mobile Native apps, with impact on / of IoT (Internet of Things) and Big Data.

See my blog for more details - https://essenceoftesting.blogspot.com/2017/10/analytics-forgotten-child.html

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The What, Why and How of Analytics Testing

  1. 1. THE WHAT, WHY & HOW OF WEB ANALYTICS TESTING Anand Bagmar Software Quality Evangelist
  2. 2. ABOUT ME @BagmarAnand about.me/anand.bagmar
  3. 3. Analytics Web / Mobile / ...
  4. 4. WHY DO WE NEED ANALYTICS?
  5. 5. WHAT IS ANALYTICS?
  6. 6. ANALYTICS SOLUTIONS Google Analytics SiteCatalyst Amplitude WebTrends ….
  7. 7. Is that all to Analytics?
  8. 8. The new “kids” in town IoT & Big Data teenagers
  9. 9. Some popular use cases https://www.kaaproject.org/iot-use-cases/
  10. 10. IOT – INTERNET OF THINGS Opportunity to ¨ Create new value propositions ¨ Be Innovative & Creative
  11. 11. IOT – HOW TO DELIVER VALUE? ¨ Automate the manual processes ¨ Integrate data capabilities ¨ Collect – integrate from various sources ¨ Repeat collection – automate the collection ¨ Analyze – manual & machine learning ¨ Optimize / Pivot ¨ Repeat
  12. 12. IOT – CHALLENGES ¨ Federated devices, ¨ Different types of networks ¨ Different communication channels ¨ Physical (hardware) & Virtual (software)
  13. 13. IOT – BIGGER CHALLENGES ¨ Too many devices ¨ Lots of data
  14. 14. BIG DATA …. IS GETTING BIGGER ¨ Volumes of data generated ¨ A jet engine generates 1TB of data per flight. ¨ A large refinery generates 1TB of raw data per day. ¨ As cars get smarter, the number of sensors is projected to reach as many as 200 per car. ¨ Sensors of all types will generate immense amounts of data. In fact, analysts estimate that by 2020, 40 percent of all data will come from sensors. ¨ IoT leads to massive volumes of data http://www.cisco.com/web/solutions/trends/iot/docs/iot-data-analytics-white-paper
  15. 15. What does all this mean for Testing?
  16. 16. TESTING OPPORTUNITIES ... ¨ Build capabilities (and tools) to validate – ¨ Data collection is working well ¨ From all sources ¨ Analyzing data, capturing patterns and trends ¨ Optimize business value ¨ Create new opportunities and value propositions
  17. 17. TESTING OPPORTUNITIES ¨ “Testing” of these new integrations & its value propositions ¨ Performance ¨ Reliability ¨ Security ¨ Scale
  18. 18. You don’t need to think complex!!
  19. 19. VIU ¨ Unique installs (Android) - > 1.75M ¨ Unique # of devices (Android) - > 13K
  20. 20. Testing Analytics
  21. 21. TESTING AT THE REPORT LEVEL Pros ¨ Ensure report is setup correctly Cons ¨Licensing ¨Reports not yet setup ¨Validate all requests are sent / captured
  22. 22. Biggest Problem It is TOO LATE!
  23. 23. The Solution
  24. 24. Analytics Testing Challenges
  25. 25. MANUAL
  26. 26. REPEATING OVER-AND-OVER AGAIN
  27. 27. BATCHING
  28. 28. The Automation Solution
  29. 29. WAAT - Web Analytics Automation Testing
  30. 30. WHAT DOES WAAT DO FOR ME? q Plugs into existing Test Automation Framework q With minimal changes q Web Analytic tool independent q UI Driver framework independent q Browser independent q Works for Native apps as well mobile-web (Android / iOS)
  31. 31. @BagmarAnand about.me/anand.bagmar THANK YOU
  32. 32. RESOURCES ¨ https://github.com/anandbagmar/waat ¨ https://github.com/anandbagmar/waat-ruby ¨ http://essenceoftesting.blogspot.in/search/label/waat ¨ http://www.cisco.com/web/solutions/trends/iot/docs/iot-data-analytics- white-paper ¨ http://www.dezyre.com/article/how-big-data-analysis-helped-increase- walmart-s-sales-turnover/109

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