This deck was the basis for a talk about big data product management I gave at Big Data Mornings (@BigDataAM) in Atlanta at @Hypepotamus on Wed August 28, 2013.

1. You don’t need to be a data scientist but it helps!
J. Travis Turney, MBA
Co-founder @DataScienceATL

2. Big Data Product Management
Vision What does success look like?
Data What data do you have/need?
Tools What do you need to get there?
Execution Who’s going to make it happen?

3. Vision
What is the business problem you need to solve?
Revenue growth?
Cost control?
What valuable answers are you seeking in the data?

4. Know your data!
How large is the data to be stored?
How large is the data to be queried?
What time frame is appropriate for the response?
How fast is it arriving (bursts or continuously?)

6. Figure provided courtesy of Brad Anderson, Solution Architect,

7. Tools – Structured data
Structured Query Language (SQL)

8. Tools – Unstructured (NoSQL)
What if your data isn’t structured?

9. Tools – Unstructured (NoSQL)
NoSQL vendors

10. Tools – Streaming

11. Tools – Batch processing
Hadoop – “Horizontally scalable” distributed
platform

12. Execution – How to get
started?
SQL skills are everywhere. Lots of talent. Easy to hire.
Hadoop skill set growing but talent can be expensive
NoSQL talent is rarer than Hadoop
Streaming skills may be the most rare

13. So Where Can I Find Talent?
@DataScienceATL meetup
Monthly events with local data science thought
leaders
Great opportunities to sponsor, network, & recruit!
www.meetup.com/Data-Science-ATL/