Data Observability Use Cases
Data observability uses techniques adapted from governance and application performance management
tools to study the health of modern data environments. This emerging discipline includes data quality
observability, which studies the performance of data pipelines as well as the infrastructure that support
them. Data observability programs and solutions should address these ten use cases across four
categories:
Prepare: Infrastructure design, pipeline design, and capacity planning
Operate: Data quality, data drift, performance tuning
Adjust: Resource optimization, storage tiering, migrations
Fund: Financial Operations (FinOps)
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