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Big data trap

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Don't fall in the big data trap key principles

Don't fall in the big data trap key principles

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Transcript

  • 1. Big Data trap francis@qmining.com @fraka6
  • 2. Data/Big Data Knowledge Action People care about Knowledge/actions not data
  • 3. Agenda ● Big data dilemma ● When are we doing Big Data? ● Maturity/Evolution steps ● The big data trap ● Optimal design = real time data-mining ● Increase your chances of success
  • 4. The Big Data Dilemma
  • 5. Big Data = Data + IO bounded (disk) CPU <100%Data IO bounded
  • 6. QA BI Maturity Barriers of entry Levels Just another barrier of entry
  • 7. Trap = no KPI ● No KPI -> batch processing -> big data ● KPI -> real time -> no big data complexity
  • 8. Optimal design = real-time data-mining ● Events -> everything is an event ● + Rule -> create signal from events ● + KPIs -> selection of signals (top level) ● + Incident = signal static/dynamic thresholds ● + Root causes analysis ○ Bayesian inference (ratio signal) ○ Signal correlation (std signal) ○ Rule filtering (domain specific)
  • 9. Increase chances of success ● Data driven culture ● Data quality culture (Avoid logs) ● Reach Analytics/BI level ● KISS
  • 10. Recap ● Big Data = Small Data + IO bound ● Big data->Data->Analytics->Mining->Predictive ○ Data Quality = BIGGEST PROBLEM ○ Big Data = another barrier of entry ● Big data trap = no KPI ● KISS = real time data mining
  • 11. hum... Questions? francis@qmining.com