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Successful Migration to Azure Cloud Platform For SSIS Workflows

  • Location : Bellevue, WA, United States
  • Industry : Information Technology

Project Summary

Our client is a technology consulting firm offering various business services for organizations worldwide. Their solutions include Azure, Business Intelligence, Advertising & Marketing, Solution Assessments, and Staffing. We help our client successfully migrate on-premises SSIS to Azure using Azure Data Factory with intelligent triggers for automated execution. Evaluated and migrated C# scripts to Azure Synapse pipelines or Azure Functions for enhanced maintainability. We Optimized executables, moving the On-Premises SQL Server to the Azure SQL Server for scalability. Migrated SSIS reports to Power BI, improving data exploration and optimized stored procedures for enhanced performance.

Insurance-Client-Challenges

Challenges

Our client had an on-premises system/infrastructure that included SSIS packages, reports, and data that come with the following particular challenges:

  • Capital Expenditure: On-premises infrastructure demands substantial upfront investments in hardware, software, and networking, straining the organization’s capital budget.
  • Limited Scalability: Scaling on-premises infrastructure was slow and expensive, posing challenges in rapidly responding to increased demand or data volume surges.
  • Maintenance & Upkeep: Ongoing maintenance of on-premises systems, involving hardware upgrades, software updates, and troubleshooting, necessitates a skilled IT staff for management and support.
  • Resource Utilization Efficiency: On-premises infrastructure often requires over-provisioning to handle peak workloads, leading to lower overall resource utilization during periods of lower demand.
  • Limited Accessibility: On-premises systems are inaccessible, especially if the organization has multiple locations or remote workers. This was causing hindrance in collaboration and access to data from different locations.
  • Disaster Recovery & Business Continuity: Implementing effective disaster recovery and business continuity plans was becoming more challenging with their on-premises system.

Solutions

Acme One provided a solution comprising of the following to address the aforementioned challenges:

  • Successfully migrated on-premises Microsoft SQL Server Integration Services (SSIS) to the Microsoft Azure Cloud Platform using Azure Data Factory, ensuring a smooth transition of data workflows to the cloud environment.
  • Implemented intelligent triggers within Azure Data Factory to replace the traditional job-based approach for executing SSIS packages. This automation ensures the timely and seamless execution of data workflows, reducing manual intervention.
  • Evaluated the existing custom scripts within SSIS tasks, written in C#, and intelligently migrated them to either Azure Synapse pipelines or Azure Functions based on the suitability of the proposed solution/technique. This modernization enhances maintainability and takes advantage of cloud-native features.
  • Analyzed and converted numerous executables written in C# and previously executed by Skybot jobs. The migration involved carefully considering time and complexity to determine whether Azure Synapse pipelines or Azure Functions were more appropriate. This optimization results in improved efficiency and cost-effectiveness.
  • Successfully migrated the On-Premises SQL Server to Azure SQL Server, providing a scalable, secure, and managed data platform for the organization’s data needs.
  • Migrated existing SSIS reports to Power BI, leveraging the benefits of a more modern and user-friendly reporting platform, enabling enhanced data exploration, analysis, and decision-making.
  • Optimized existing stored procedures for enhanced performance.
Genre-Insurance-Solution

Results

The outcome of our provided solution has helped the client in the following manner:

  • Azure Synapse Analytics: Offered scalable data storage and analytics, allowing the organization to handle growing data volumes and accommodate increased demand for analytics processing.
  • Pay-as-You-Go Model: Azure services typically operate on a pay-as-you-go model. Hence, it provided cost efficiency by allowing the company to pay for the resources they consume.
  • Azure Data Lake: Serves as a centralized and scalable repository for diverse data types, promoting a unified platform for storage and analytics.
  • Integration with Azure Services: Facilitates seamless integration between Azure services, creating a unified and cohesive data environment.
  • Azure Data Factory: Provides a cloud-based data integration service for orchestrating and automating data workflows, offering modern alternatives to on-premises SSIS packages.
  • Azure Synapse Analytics: Supports advanced analytics, enabling powerful data processing and analytics capabilities.
  • Power BI: Enhances data visualization and reporting, allowing for more insightful and interactive analytics. It allowed easy sharing of interactive reports and dashboards, improving collaboration across the organization.
  • Real-time Data Processing: Azure services, including Azure Synapse Analytics, support real-time data processing, allowing the company to make decisions based on the most current information.
  • Cloud-Based Accessibility: Allows users to access data and reports from anywhere with an internet connection, promoting global accessibility and collaboration.

Tech Stack

  • SSIS
  • Azure SQL
  • Azure Data Factory
  • Azure Synapse Analytics
  • Azure Function App
  • C#
  • .NET Framework
  • Power BI
  • Azure Data Lake
  • Azure Key Vault
  • DevOps
  • Git
  • Spark Notebook

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