This document discusses big data and provides advice for increasing chances of success working with big data. It defines big data as data that is input/output bound rather than CPU bound. It notes that big data presents another barrier to entry, especially for small and medium businesses, and recommends establishing a data-driven culture, focusing on data quality, and targeting consumer-facing rather than business-to-business applications to help overcome challenges. The document also outlines typical maturity steps from data to analytics to data mining to predictive analytics.

1. Big Data:
Just another barrier of entry
francis@qmining.com
@fraka6

2. Big Data Knowledge Action

3. Unhidden Agenda
● When are we doing Big Data?
● Big Data market
● Maturity/Evolution steps
● Increase your chances of success

4. Big Data =
Data + IO bounded
CPU
<100%Data
IO bounded

5. The Big Data Dilemma

6. Big Data Dead Valley
TechnoMaturtity/
Risk
Enterprise size
SMB
Enterprise
Start-ups
Techno Maturity
Risk

7. QA
BI
Maturity
Barriers of entry Levels

8. Data Access & Quality
User data privacy, IT outsourcing protection, Data Quality

9. Increase chances of success
● Data driven culture
● Data quality culture
● Reach Analytics/BI level
● B2C over B2B/B2B2C
● Avoid logs

10. Recap
● Big Data = Small Data + IO bound
● Big Data market = Startup or Enterprise
● Data->Analytics->Mining->Predictive
● Data Quality = BIGGEST PROBLEM
● Big Data = another barrier of entry

11. hum...
Questions?
francis@qmining.com