EVENT DATA MODELING MEASURECAMP LONDON ‘16
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EVENT DATA MODELINGMEASURECAMP LONDON ‘16
MEASURECAMP LONDON ‘16
WHO’S CAPTURING ATOMIC DATA?
Who’s using GA Premium, Adobe, Snowplow, Segment, … to capture atomic or event-level data?
How is the data made available, consumed, turned into insights?
MEASURECAMP LONDON ‘16
WE ALL LIKE ATOMIC DATA…
With current technologies, we can record all user interactions, across all channels, store it in our own data warehouse, and join it with all other datasets we have.
… BUT IT REMAINS HARD TO CONSUME
MEASURECAMP LONDON ‘16
EXAMPLE 1
Event stream:
‣ Pre-roll loaded, clicked, skipped, …
‣ Main video loaded, paused, …
‣ Interactions within the video
‣ Subscribe, like, share, comment, …
‣ Much, much more
MEASURECAMP LONDON ‘16
EXAMPLE 2
Event stream:
‣ Tutorial start, tutorial finish
‣ Start game, change difficulty
‣ Level up
‣ Purchase
‣ Invite friends
‣ Much, much more
MEASURECAMP LONDON ‘16
WHY IS IT HARD TO CONSUME?
Events need to be looked at in context, and in the right order, to become valuable.
End users cannot be expected to do the complex transformations that are required to draw insights from the atomic data.
“EVENT DATA MODELING IS THE PROCESS OF USING BUSINESS LOGIC TO AGGREGATE AND TRANSFORM EVENT-LEVEL DATA TO PRODUCE MODELED DATA THAT IS SIMPLER TO CONSUME”
DEFINITION
MEASURECAMP LONDON ‘16
EVENT DATA MODELING
BEFORE DATA MODELING
DATA IS IMMUTABLE AND UN-OPINIONATED
AFTER DATA MODELING
DATA IS MUTABLE AND OPINIONATED
MEASURECAMP LONDON ‘16
EVENT DATA MODELING
▸ ID stitching
▸ Macro events
▸ Units of work
▸ Sessions
▸ Users
THOUGHTS OR QUESTIONS?WE’RE HIRING JUNIOR DATA
ANALYSTS
MEASURECAMP LONDON ‘16
EVENT DATA PIPELINE
PROCESSINGCOLLECTION
REAL-TIME APPS
REAL-TIME DASHBOARDS
DATA EXPLORATION
PREDICTIVE MODELING
DATA WAREHOUSE
WEB
APPS
SERVERS
3RD PARTY
IOT
MEASURECAMP LONDON ‘16
EVENT DATA PIPELINE
PROCESSINGCOLLECTION
REAL-TIME APPS
REAL-TIME DASHBOARDS
DATA EXPLORATION
PREDICTIVE MODELING
DATA WAREHOUSE
WEB
APPS
SERVERS
3RD PARTY
IOTMANY SOURCES
MEASURECAMP LONDON ‘16
EVENT DATA PIPELINE
PROCESSINGCOLLECTION
REAL-TIME APPS
REAL-TIME DASHBOARDS
DATA EXPLORATION
PREDICTIVE MODELING
DATA WAREHOUSE
WEB
APPS
SERVERS
3RD PARTY
IOTONE PIPELINE
UNIFIED LOG, NO SILOS
MEASURECAMP LONDON ‘16
EVENT DATA PIPELINE
PROCESSINGCOLLECTION
REAL-TIME APPS
REAL-TIME DASHBOARDS
DATA EXPLORATION
PREDICTIVE MODELING
DATA WAREHOUSE
WEB
APPS
SERVERS
3RD PARTY
IOT
VALIDATION ENRICHMENT DATA MODELING
ONE PIPELINE UNIFIED LOG, NO SILOS
MEASURECAMP LONDON ‘16
EVENT DATA PIPELINE
PROCESSINGCOLLECTION
REAL-TIME APPS
REAL-TIME DASHBOARDS
DATA EXPLORATION
PREDICTIVE MODELING
DATA WAREHOUSE
WEB
APPS
SERVERS
3RD PARTY
IOT
MANY CONSUMERS
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