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Bouygues Telecom

CASE - PREDICTION OF ANOMALIES

Data Factory/

We're proud
of our Work!

CLIENT
SKILLS & ROLES

A service centre of 9 people
1 Project Manager
4 Developers (including 1 lead)
4 DevOps (including 1 lead)

TECHNICAL STACK

Java, Spark, Tenserflow, HDFS, ElasticSearch, Kafka, Hive, Cassandra, Hortonworks, Docker, Ansible, Kubernetes.

KEY FIGURES
5
PETAOCTETS

of aggregated data

77
NODES

deployed

150k
EVENTS/SEC.

on the real time part

WHAT IS THE CHALLENGE?

Accompanying the Bouygues Telecom CIO to improve QOS through the detection and prediction of anomalies thanks to big data.

 

WHAT ARE WE TALKING ABOUT?

With the aim of improving service quality, our teams aggregate, transform and restore data from all Bouygues network equipment (internet box, smartphone, routers, etc.).
This data is then used in 2 different ways: for real-time dashboards or via BI tools and machine learning algorithms (for anomaly prediction).

 

WHAT ABOUT DELIVERY?

In charge of all project phases (monitoring, design, implementation and maintenance), we make recommendations with customer validation.
The infrastructure being on premise, we control our infrastucture in the smallest details and mount the management and automation solutions ourselves.

Our experts

Thomas Leger

Alexis Lustenberger