Client
The client is a leading Belgian insurance company providing life insurance, non-life insurance and supplementary pensions. Established in 1824, the company serves private individuals, self-employed persons, SMEs, and large enterprises. To modernize their data infrastructure and improve analytics capabilities, the client aimed to migrate their data warehouse to Azure, ensuring scalability and efficiency for future business needs.
Challenge
The client’s existing SAS-based data warehouse was not scalable to meet the evolving business requirements. Multiple processes running on disparate systems (SAS DI and SQL Server Integration Services) lacked integration, leading to inefficiencies. As part of their digital transformation journey, the client sought to transition to a cloud-based data warehouse on Microsoft Azure to improve data accessibility, enhance reporting capabilities, and optimize operational efficiency.
Key challenges included:
- Data quality issues and fragmented infrastructure for operational and analytical workloads.
- Performance bottlenecks, particularly during peak usage at financial closing periods.
- Limited business user access to critical data for decision-making.
- The need to minimize downtime and disruption during migration.
Solution
Hexaware implemented an automated cloud migration strategy leveraging its Amaze® for Data & AI platform. The approach focused on streamlining data ingestion, enhancing processing efficiency, and ensuring a seamless transition to Azure.
The solution included:
- Developing a metadata-driven data ingestion framework on Azure to support both batch and real-time data pipelines.
- Creating a centralized data repository to store data related to life insurance, non-life insurance, employee benefits, and IT document management, serving as a golden source for analytics and reporting.
- Establishing a multi-layered data processing architecture (L0, L1, L2), with archival storage in Azure Blobstore to ensure data integrity and accessibility.
- Automating the assessment and migration of existing 2200+ ETL jobs from SAS DI & SQL Server Integration Service to ADF (Azure Data Factory).
- Integrating Azure Synapse for advanced analytics and reporting while orchestrating jobs through ADF.
- Ensuring seamless report repointing and validation with minimal disruption to business operations.
By adopting an Azure-native, automation-led approach, Hexaware enabled the client to accelerate cloud adoption while ensuring data integrity, scalability, and enhanced business intelligence capabilities.
Benefits
Hexaware’s strategic approach to data warehouse migration delivered significant operational and cost efficiencies for the client. By leveraging an automation-led framework and a structured data warehouse assessment, the migration process was streamlined, ensuring minimal disruption and maximum value.
The benefits included:
- 50% reduction in assessment timeline, accelerating the overall migration process.
- 3x more efficient factory model, ensuring consistency, reducing risks, and improving migration accuracy.
- 40-50% increase in cost-effectiveness, optimizing resources and reducing operational expenses.
- Seamless integration of ADF and dataflow, enabling efficient data processing and transformation.
- On-demand compute, storage, and ETL provisioning, ensuring scalability and flexibility for future business needs.
- Lower Total Cost of Ownership (TCO) through optimized infrastructure and cloud-native efficiencies.
By successfully executing the data warehouse migration to cloud, Hexaware empowered the client with a scalable, high-performance data environment, enhancing business intelligence and decision-making capabilities.
Summary
Hexaware enabled a leading Belgian insurance company to migrate its data warehouse to Azure, enhancing scalability, efficiency, and cost-effectiveness. Through an automated cloud migration approach, the client achieved faster data processing, reduced risks, and improved analytics, ensuring a seamless transition to a cloud-based data warehouse with minimal disruption.
