The event will feature Andy Petrella, Co-founder of Kensu (formerly Data Fellas), who will take us through a journey of how to use Scala for doing interactive programming, distributed programming and machine learning. The talk will cover what Data Science applied to the Enterprise means, the challenges, the takeaway and the expected advantages. In accord with the constraints imposed by real life businesses, we’ll have a demonstration of an environment focused on production readiness preserving the capacity to prototype, enabling deployment and favouring continuity. We’ll close the debate with a note about the next challenges: how to ensure the maintainability, the data governance and the perennity and evolution of knowledge in a long life Enterprise with a growing number of datasets, data, data scientists, processes and use cases. Meetup event: https://www.meetup.com/Data-Science-Milan/events/235594132/

1. Kensu
Data Science for the Enterprise

2. Kensu
Created in 2015
Mission:
Lifting Data Science to the
Enterprise level
Product:
ADALOG
Team
Andy Petrella
Math, Spark Notebook
Xavier Tordoir
Physics, Genomics
2 -> 11 scientists in 2016
Plenty of positions more in 2017

3. Data Science Team minded
Platform dedicated to data
science team
Using production data
Including tooling
prototyping (local)
project (distributed)
Test Accept Prod
Data Science
Spark
Mesos
HDFS Cassandra
Kafka
Spark-Notebook
JupyterCloudian
Marathon
Chronos
Git Artifactory
Enterprise

4. Production oriented
Integration of the whole
production toolchain (in scala /
JVM)
Satisfying the established
processes
One-click deployment
Schema oriented micro services
Extensibility (support for
libraries, …)
Test Accept Prod
Data Science
Spark
Mesos
HDFS Cassandra
Kafka
Spark-Notebook
JupyterCloudian
Marathon
Chronos
Git Artifactory
Enterprise

5. Context awareness
Data lineage
Data statistics live-harvesting
Automatic pipelining
User awareness
Use case awareness
Runtime awareness
Open SDK (integration with all
data science tools)

6. Efficiency catalyser
Data recommendation
Model recommendation
User recommendation
Quality monitoring
Root cause analysis
Risk analysis
and more…

7. DEMO!
(probably long ^^)
(there are/will be some pizza…)

8. Stay tune (@kensuio)
Demo accesses on the way
Specially for O’Reilly trainees

9. We’re hiring!
http://kensu.io
contact@kensu.io

10. Kensu
Data Science for the Enterprise
Q/A