Construction

Go to Cloud DataOps & FinOps oriented

#Cloud Data Architecture
#Azure
#FinOps

#Ambition

Ambition
of the mission

How to change the technological environment of a large group, where multiple teams, each with their own tools, methods and data perimeters, collaborate? The evolution of our client's uses and technological needs (IoT, real time, AI...), as well as a growing data ambition, quickly imposed the need for a complete overhaul of its data ecosystem, in order to converge on unified practices and a unique technological base.

#Method

Our
approach

Think

Offer a unique enterprise-wide data vision

Our challenge: to understand and reconcile the constraints and objectives of all the business departments concerned. For this, only one possible solution: rationalize the technological landscape and converge on a single platform. Since the resulting environment was the group's first cloud initiative, it was then necessary to define, in consultation with the IT teams, security and interface standards with on-premise data centers, the basis for the company's future Azure uses!

Make

Design a flexible but controlled platform

The delivered project is based on a Snowflake DWH, allowing each team to keep control of their data while maximizing the sharing of the group's data assets. This platform made it possible to implement a DataOps strategy for the development and continuous improvement of ETL flows and the data model, as well as cost management and optimization centered on user accountability.

Scale

Empowering business teams, through a self-service approach

This technological and methodological paradigm shift has mechanically induced a need for coaching and support for teams. In order to streamline this transition, change support was proposed: formalization of best practice frameworks, redefinition of governance, training for users and administrators... This approach allowed the establishment of a “Data Factory” type organization, to support the long-term projects and technological developments of the platform.

#Benefits

Indicators
of success

Reconciliation of uses enterprise-wide data

Modernizing methods development via a DataOps approach

Significant performance gains and reliability across the entire data platform

#DataStories

Discover our
other use cases

See all our use cases