About Client
Our client is a financial services firm based in London, United Kingdom. The company provides financial solutions tailored to modern needs by leveraging insights from global markets and emerging trends to develop financial products and services to help both HNI (High Networth Individuals) and organizations to achieve their wealth management and strategic investments
Problem Statement
The company uses SQL Server Integration Services (SSIS) to handle various data integration tasks, such as extracting data from diverse sources, transforming and cleansing it, and loading it into data warehouses and data marts. Currently, hundreds of SSIS packages run on multiple on-premises servers, managed through SQL Server Agent jobs. This setup results in high operational and maintenance costs, with a suboptimal cost-to-performance ratio
Project Challenges
- The on-premises SSIS servers had limited resources and could not handle the increasing data volume and complexity.
- The SSIS packages had limited visibility and monitoring, which made it hard to troubleshoot and optimize them.
- The SSIS packages had dependencies on external components and configurations, such as drivers, connections, and proxies, which made them difficult to migrate and manage.
Versich Approach and Solution
Migration to Azure Data Factory:
To enhance efficiency and reduce operational overhead, we migrated the company's SSIS workloads to Azure Data Factory (ADF), a fully managed cloud service for data integration. This transition offers the following key benefits:
- On-Demand Scalability: ADF allows the company to provision and scale Azure-SSIS Integration Runtime (IR) clusters as needed, eliminating the burden of managing and maintaining on-premises infrastructure and associated licensing costs.
- Seamless Migration: With tools like the SSIS Job Migration Wizard in SQL Server Management Studio (SSMS) and Azure-enabled SQL Server Data Tools (SSDT), the company migrated its existing SSIS packages to the cloud with minimal modifications.
- Enhanced Integration: ADF integrates SSIS packages with other Azure services such as Azure Data Lake Storage, Azure Synapse Analytics, and Azure Monitor. This expands the company's data integration capabilities and unlocks new features.
- Streamlined Management: ADF provides an intuitive user interface for managing, monitoring, and debugging SSIS packages and pipelines. Additionally, its REST API and PowerShell cmdlets enable automation and orchestration, simplifying day-to-day operations.
This migration positions the company to leverage the scalability, flexibility, and cost-efficiency of a cloud-native data integration platform.
Positive Business Impacts
- Improved Efficiency and Reliability: By scaling Azure-SSIS IR clusters dynamically based on data volume and complexity, the company achieved an 80% improvement in performance and reliability. Azure Data Factory's high availability and fault tolerance further ensured seamless and dependable operations.
- Enhanced Collaboration and Capabilities: Integration of SSIS packages with Azure services like Azure Data Lake Storage, Azure Synapse Analytics, and Azure Monitor enabled advanced features such as data lake integration, data quality monitoring, and data lineage tracking, driving improved collaboration and insights.
- Faster Time to Market: The migration to Azure Data Factory streamlined data integration processes, reducing the time required to build, deploy, and modify data pipelines. This allowed the company to respond more quickly to business needs and accelerate the delivery of data-driven insights.
- Cost Efficiency: The company reduced operational and maintenance costs by 50% by eliminating the need for on-premises SSIS servers and licenses. With Azure-SSIS IR clusters, the company pays only for the resources used, significantly optimizing cost management.
