To participate in this group, please answer some of the following questions.

1. How and when did you become interested in analytics?
2. Do companies treat data and data science differently in Europe, America and Asia?
3. What are your predictions for the next 5 years, regarding the evolution of data science?
4. Is there still interest in small data, classical statistical models, simulation and sampling?
5. Are poor models on comprehensive data better than great models on silos?
6. How to get data silos, internal and external data sources, to blend together?
7. What skills should data scientist acquire? 
8. What should colleges teach?
9. I believe great data scientists are also good management consultants. Do you agree?
10. Which areas are going to benefit most from cloud technology?
11. What is the difference between computational statistics and data mining?
12. With the advent of huge data, what is the future for QA, fuzzy merging, data compression, sampling, interactive dashboards and smart visualization?
13. Is there a lot of hype surrounding real time analytics?
14. Do you think in-memory analytics will become more widespread? What would make in-memory analytics and in-database data mining more attractive?
15. Will the data become more or less structured?
16. What do you think of companies heavily relying on social media for data intelligence? Aren't social users different, possibly more liberal, than others?
17. What about security, regulation and privacy issues?
18. What about automating the process of analyzing big data?
19. Is the return on big data bigger than on small data, once you factor in infrastructure, learning curve and human resources? How to improve return on investment?
20. What are the competitive advantages offered by your company?