Data at daily business. Showcasing how/why to use Keboola Connection for data integration and development together with Tableau, GoodData, Chartio, YellowFin, etc. I believe that the whole trick is to change the game. Change how "normal" business people consume data and make decisions in daily practice. As McPen - they changed store keepers into Data Analytics and grew their EBITDA 2x /y in totally offline traditional business!

1. Keboola Connection
Enterprise Tech MeetUP London
Pavel Dolezal
@pabu01

3. What is KBC ?
Think about it is a Data Lego
KBC is a data production environment agile development of
data based products I/O
● DataWarehouse
● ETL (own extractor framework)
● JSON parser
● sandboxes (MySQL, Redshift, R, Snowflake.net)
● staging layer
● transformation templates
● Docker based provisioning of 3rd party components
● Data Appstore - predictions, insights

4. Why KBC
● Open architecture
● Built for work
● Highly used/criticised - shaped by cust feedback
● Flexible - not built on one particular tech, but rather
always possibility to select what is most suitable for the
job
● Your IT has a full power over KBC
● Live eco system of add on apps and developers
● Multiple destinations (GD, Chartio, YF, Tableau)
● Storage API - consume data in SAS, Tableau, RStudio or
anywhere

5. How do I save with KBC
● Tech team able to focus on the core business
● Ready for exponential growth
● We focus only on our part and try to be the best at it so
you don’t have the data headaches
● Reusability of “code”
● Easy SQL based environment so you can swap senior
people to junior
● Business can build and take care of the product itself with
a low overhead on IT department => agile

7. INTEGRATION

8. Keboola Connection
Orchestrator/scheduler
Storage
(+Audit, Access
management)
Transformations
Recipes (Apps)
Extractors /
API input
Writers / API
output
3rd party services
Data source /
systems
Data
Consumption

9. EXTRACTORS TRANSFORMATION WRITERS
Query based environment
- languages SQL / R
- Sandboxes
- Logic Data model builder and
visualisator
STORAGE - JOBS - ORCHESTRATIONS
Applications -> Recipes
- basket analyses
- correlation finder
- grouped histograms
- Linear dependencies
- etc...

10. McPen - shop assistants work with retail data every day and
decide basket up-sales, promo items, etc.