Tools span the following categories, each of which plays a part in the data lifecycle. Vendors address these categories with both pure play products and suites.

• Data integration automates the design, development, management, monitoring, and adaptation of pipelines.
• Transformation manipulates data in creative ways to address new use cases such as data-driven applications.
• DataOps optimizes pipelines with continuous integration and continuous delivery (CI/CD), testing, and monitoring.
• Data observability tracks and helps optimize pipeline performance and data quality.
• Orchestration integrates pipelines with applications to kick off operational tasks.
• Reverse ETL helps operationalize data by integrating data warehouses with applications.

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