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Become agile and data-driven through the power of artificial intelligence and machine learning

Background

Our client is one of the largest financial institutions in Belgium with more than 700 branches, 7,000 employees, and more than 3.5 million customers in segments across individuals, families, self-employed, professionals, and entrepreneurs.

Challenge

Our client wanted to facilitate the delivery and discovery of new data sources to accelerate their digital transformation. They wanted to create a robust data lake cluster, built on best practices, to process large amounts of data faster and more effectively. Additionally, they wanted a supporting architecture in line with the modern data governance and processing strategies.

Approach

- Understand and assess the current environment and define best practices to build on. - Reconcile the IT standards and security with the design of the big data approach. - Iterative implementation and deployment of the cluster to test the defined procedures. - Fast development of a relevant business use case. - Define and embed governance procedures as part of the platform operations.

Key results

01
Modern data governance framework
02
Business case driven iterative implementation approach
03
Experienced big data architects and subject matter experts

Benefits

The organization now has a more precise and accurate model to support operational decision-making. They were able to reduce end-to-end processing time from 24 hours to 20 minutes by means of distributed processing. Data scientists have a dedicated sandbox environment to experiment and identify potential business gains, and they can deploy new insights and learnings much faster, accelerating their path to becoming a data-driven company.

Technology partners

Microsoft

Microsoft is a cloud provider and publisher of office software and business intelligence solutions.

25+

years of Gold partnership agreement

3x

Certified expertise: application development, data analytics, cloud platform

200+

clients

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75 Queen St. – Suite 1400 H3C 2N6– Montréal, Québec