ABN AMRO's Azure-First Data Strategy for Enhanced Business Decisions
Technology Category
- Analytics & Modeling - Big Data Analytics
- Analytics & Modeling - Machine Learning
Applicable Industries
- Buildings
- Finance & Insurance
Applicable Functions
- Warehouse & Inventory Management
Use Cases
- Mesh Networks
- Tamper Detection
Services
- Data Science Services
- System Integration
About The Customer
ABN AMRO is the third-largest bank in the Netherlands, with over 100 branch offices and more than 30,000 employees. The bank's mission statement, 'Banking for better, for generations to come,' is embodied by the way it uses digital services and data to support customers during key life moments. The bank processes a diverse and complex range of data daily, including data from business process management, HR systems, financial systems, customer systems, marketing systems, and commercial systems, as well as recorded conversations and correspondence with clients.
The Challenge
ABN AMRO, the third-largest bank in the Netherlands, was facing challenges with its on-premises servers. The bank, which processes a diverse and complex range of data daily, needed a more efficient and reliable way for its teams to access and contribute data. The bank's existing system, while secure and capable of handling millions of transactions daily, was not providing the speed and reliability required for efficient data access. The bank's data types ranged from business process management, HR systems, financial systems, customer systems, marketing systems, and commercial systems, to recorded conversations and correspondence with clients. The challenge was to find a solution that could handle this high variety of read patterns, duplicate data, and maintain control.
The Solution
ABN AMRO turned to Microsoft Azure for a solution. The bank migrated to the cloud, which offered greater scalability, ease of access, and a suite of Azure services to empower both customers and functional teams. The bank embraced a data mesh architecture on Azure, which allowed it to unlock data insights and drive business decisions. Azure Data Lake Storage and Azure Cosmos DB were used to meet the challenge of facilitating a high variety of read patterns while duplicating data and maintaining control. The bank also used Azure Data Lake Storage and the Parquet file format to make data readily available to a wide range of Azure services, including Azure Databricks and Azure Synapse. This allowed the bank's team to access data without having to process it into different formats.
Operational Impact
Quantitative Benefit
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