Top 10 Big Data Systems Pitfalls - war stories and lessons learned

Do you want to hear war stories about the design and implementation of Big Data solutions? Have you ever wondered why Big Data ecosystem is changing so rapidly and is not yet stable? How to choose proper technologies and solutions which can achieve project goals? I do not promise any silver bullets. I simply want to share my experience gained during last 5 years of crafting data intensive applications.

What I will talk about in details:

1. Biggest data issues that companies are struggling with

2. Choosing a proper business domain to start Big Data projects

3. What technologies can be used as a standard toolbox to address and solve typical Big Data problems?

4. How Big a Big Data really is? Can it fit in Excel spreadsheet? Why in most cases 99.7% accuracy of the results is good enough?

5. What steps should a company take to properly develop a data platform

6. Why Lambda architecture is a good old friend

7. How to address all users including analysts, developers, managers, board members, testers?

8. OLAP cubes - why do we need it? Does it have to cost a lot of $$$? Is open-source mature enough? Is it competitive with commercial vendors?

9. How fast is your realtime data processing? Do we all think about the same business use-cases?

10. Biggest misunderstandings between business and developers. How to avoid them and properly share responsibilities

Scheduled on Friday from 13:30 to 14:20 in Room 2