Credit Agricole is one of the world’s largest cooperative financial institutions, with operations in more than 50 countries and providing a diverse set of financial services including retail banking, cooperative banking, investment banking, private banking, wealth management, and asset management. In this post I’ll describe how the Credit Agricole Corporate and Investment Banking Division (CACIB) leveraged data virtualization to build a logical data fabric that provides an efficient way of integrating data from different business silos to create a shared view of enterprise data.
Target Traversal Analytics
CACIB’s data architecture was quite complex. Every individual business process had its own BI solution and a data flow that was designated specifically for that business process. This resulted in an extremely difficult to manage architecture, with over a thousand data flows and point-to-point integrations between the data sources and consuming applications. Integrating data from two or more sources was also a challenge, since the enterprise architects always had to create an additional data storage solution to carry out such tasks.
For this reason, the bank invested in larger enterprise data storage solutions, such as domain-specific data warehouses and data lakes. This investment in larger data storage solutions simplified the architecture to some extent but the problem of data being trapped in business silos still persisted, and cross-application analytics continued to be a challenge. CACIB’s chief data management goal was to enable traversal analytics that allowed them to extract insights from data pulled from both internal and external systems. However, creating another centralized repository for this initiative, like an enterprise data lake, was not the path that the company wanted to take.
Logical Data Fabric to the Rescue of Credit Agricole
CACIB started exploring other options that enabled them to focus on scaling data access points. The company wanted a solution that acted as a data access layer for non-technical users that leveraged their existing tools. Since CACIB wanted their users to be able to access external data sources, it was crucial that all data governance and security regulations were being followed. These requirements led CACIB to the Denodo Platform. The Denodo Platform’s data virtualization capabilities helped CACIB to build a logical data fabric that acted as an abstraction layer, enabling access to multiple data systems for business consumers, hiding the complexity, and exposing the data in business-friendly formats, while at the same time guaranteeing the delivery of data according to predefined semantics and governance rules.
This logical data fabric provided CACIB with two main benefits.
- The logical nature of the data fabric made gathering data from multiple sources very easy, and it facilitated operational analytics projects such as providing real-time data for a front-office trading system.
- Secondly, the logical data fabric enabled CACIB to start various data-centric initiatives aimed at democratizing data assets and simplifying data sharing/publishing between different business departments. These initiatives enabled users to publish domain-specific data as reusable data services in multiple formats such as Simple Object Access Protocol (SOAP), Representational State Transfer (REST) and Open Data Protocol (OData) web services.
A Modern Data Integration Solution To learn more about how data virtualization can help organizations of every stripe by simplifying and accelerating access to data, see the collection of Denodo Case Studies.