What practices support automation, governance, and versioning in a Fabric data engineering project?

• A. CI/CD pipelines and version control.
• B. Manual deployments
• C. Ad hoc scripts without tests
• D. No versioning or governance

Answer: (A)

Automating the build, test, and deployment of data pipelines while keeping a controlled history is essential in Fabric data engineering. Using CI/CD pipelines automates the steps to fetch code, run tests, validate data quality, and promote changes through development, testing, and production environments. This repeatable process reduces manual errors and ensures consistent behavior across runs and environments. Version control stores every change to code, configurations, and artifacts, enabling traceability, collaborative development, and safe rollbacks when needed. Together, these practices support governance by enforcing reviews, approvals, and policy checks as part of the deployment flow, and they provide versioning for reproducibility and auditability of the data engineering artifacts. In Fabric projects, this means your pipelines, notebooks, configs, and schemas live in a repository and are deployed through automated pipelines that enforce standards and maintain an auditable history. Manual deployments miss automation and testing; ad hoc scripts without tests lack reliability; and having no versioning or governance means you cannot track changes, enforce controls, or recover from issues.