7 Benefits of a Continuous Integration Approach to Data Pipelines

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When it comes to modern software development, it’s no surprise that businesses need speed. But if you develop software too quickly, it can mean sacrificing quality, security, and compliance. DevOps and continuous integration and continuous delivery (CI/CD) are proven capabilities that help companies maintain a healthy balance between agility and quality. More and more companies are integrating DevOps into their data pipeline. Here are seven benefits of adopting a DevOps approach to your data pipeline:

  1. Reusability with Data Artifact Lifecycle Management

It’s powerful when you can treat data pipelines like a product. For data lifecycle management, DevOps/DataOps methods serve as guardrails that make it easier to test and deliver data to the production environment. A continuous feedback mechanism helps data engineers and the DevOps team to, for example, optimize data delivery pipelines, improve code quality, and reuse objects later for no-code/no-code data integration activities. construction.

  1. Generate value faster and at scale

CI/CD guarantees faster release cycles. Your team will be more productive when they can, for example, automate testing at each level of data pipeline development with CI/CD. With automation, scaling becomes easier even when the data processing workload increases overnight. CI/CD also helps ensure faster and more accurate integration for increased business value.

  1. Meet enterprise-level SLAs

CI/CD tools help you meet your service level agreements (SLAs). DevOps methods allow any data engineer to modify the data pipeline. It also ensures that only quality work goes through the drill.

  1. Collaborate seamlessly

DevOps methods and CI/CD pipelines accelerate releases by allowing teams to work in parallel. With code check-in and check-out options, multiple team members can work independently on the same objects, with fewer conflicts. With real-time feedback, data engineers can iterate faster and use automation to more easily optimize operational overhead.

  1. Control version management

Tracking software versions encourages transparency and ownership. This reduces avoidable concerns about who else is working on specific builds and other dependencies. And role-based privileges and permissions ensure the reliability and security of the data pipeline.

  1. Enable experimentation and monitoring

DevOps encourages agile experimentation. It allows you to revert to the previous version of data management at any time. This is essential when the new version does not work. Developers can also try out new technologies and tasks. With an automated alert and response system, it is easier to troubleshoot and monitor CI/CD pipelines.

  1. Prepare for DataOps, MLOps and AIOps

Depending on your organization’s data maturity level, you can apply DevOps insights to customize data products and operationalize machine learning (ML) models and artificial intelligence (AI) projects in the future.

An example of a continuous integration approach to data pipelines
Guy Carpenter, one of the world’s leading risk and reinsurance specialists, used a DevOps approach in a hybrid cloud landscape. While going through several release stages, the company can streamline and automate its data processes. In the development phase, they write a task and perform unit tests. Once validated, the code moves into the system integration test environment. Then it goes through the QA testing phase, pre-production or user acceptance performance testing, and finally, production. Thanks to automation, the whole process takes care of itself. This combines agility, productivity and efficiency to improve business results.

How Informatica Can Help You
Informatica’s cloud-native data integration solutions enable you to break down the silos between development, operations, and security to deliver a consistent experience throughout the development lifecycle.

Learn more about CI/CD pipelines or contact us to explore next steps.

Jack L. Goldstein