As businesses continue to evolve in the digital age, the management and processing of data play a pivotal role in shaping strategic decisions and operational efficiency. Legacy Extract, Transform, Load (ETL) systems such as SQL Server Integration Services (SSIS), Informatica, and IBM DataStage have long been the backbone of data integration and transformation. However, the rapid advancement of cloud technologies has presented new opportunities for organizations to elevate their data processing capabilities.
In this overview, we delve into three compelling case studies that exemplify the successful migration of legacy ETL workflows to cloud-based solutions. These ETL migrations not only address the challenges posed by aging ETL systems but also unlock the potential of the cloud to enhance scalability, flexibility, and performance.
The chosen case studies delivered by Bitwise, a leader in data management and cloud modernization solutions, provide a comprehensive perspective on different migration scenarios. Now, let’s look at three real-world customer case studies on migrating ETL to cloud.
What to Explore
ETL Migration Case Studies
1. Accelerated SSIS ETL Migration to Azure Data Factory
In this case study, Bitwise demonstrates how they assisted a client in migrating their existing SSIS ETL workflows to Azure Data Factory (ADF). The challenge was to ensure a seamless transition while optimizing performance and ensuring data integrity. Bitwise leveraged their expertise in both SSIS and ADF to streamline the ETL migration process. By rearchitecting and redesigning ETL workflows to fit the cloud-native ADF environment, they achieved increased scalability, flexibility, and reduced maintenance efforts. The success of the migration resulted in improved ETL performance and the client’s ability to harness the power of the cloud for data processing.
2. Migrate Legacy Informatica ETL Code to AWS Glue
This case study highlights Bitwise’s proficiency in migrating legacy Informatica ETL code to AWS Glue, a fully managed ETL service on Amazon Web Services. The client aimed to modernize their data processing by adopting cloud-based technologies. Bitwise tackled the migration by analyzing the existing Informatica workflows and transforming them into AWS Glue jobs. This involved optimizing the ETL logic to align with Glue’s serverless architecture, which offers benefits such as automatic scaling and cost efficiency. The successful ETL migration enabled the client to continue their data processing seamlessly in the cloud while taking advantage of AWS Glue’s capabilities.
3. Automated ETL Migration from DataStage to Azure Data Factory
In this case study, Bitwise showcases their expertise in migrating IBM InfoSphere DataStage ETL workflows to Azure Data Factory. The client’s goal was to transition from an on-premises DataStage environment to the cloud for enhanced agility and scalability. Bitwise facilitated the migration by thoroughly understanding the existing DataStage workflows and transforming them to fit the cloud-based ADF architecture. By utilizing its proprietary automation tools, Bitwise ensured a smooth transition without compromising data quality or performance. The outcome was a successful ETL migration that allowed the client to harness the benefits of cloud-based data processing with a solution architecture that minimizes Azure costs.
Using Automation to Accelerate ETL Migrations to Cloud
Considering the complexity of ETL jobs developed over time in legacy systems and the incompatibility between those systems and cloud-native services, a completely manual approach is generally not feasible to deliver successful migration projects. That’s why automation has emerged as a key enabler in the process of migrating ETL workflows to cloud-based platforms.
In conclusion, the evolution of businesses in the digital era has spotlighted the critical role of data management and processing in shaping effective decision-making and operational efficiency. Traditional ETL systems like SSIS, Informatica, and IBM DataStage have long been instrumental in data integration and transformation.However, the rapid strides in cloud technology have ushered in new horizons for organizations to enhance their data processing capabilities.
The three real-world customer case studies presented here exemplify the successful migration of legacy ETL workflows to cloud-based solutions. These migrations not only address the challenges posed by aging ETL systems but also tap into the immense potential of the cloud to augment scalability, flexibility, and performance. Check out our automated ETL migration page for a complete solution overview.
Editor's Note: The blog was originally posted on September 2023 and recently updated on September 2023 for accuracy.