As per DORA research, observability is one of the key capabilities to drive higher software delivery and organizational performance. Observability enables teams to report on the overall health of systems which ultimately helps in tracing, understanding, and diagnosing problems using key business and system metrics.
With the rise of data being used as a strategic resource for making key decisions, data observability has emerged as a critical concern. Data observability allows data engineers to spend less time firefighting and more time focusing on key data initiatives. It also results in increased trust and adoption of data products across the organization.
Data observability helps teams & organizations in monitoring the health of data by maintaining a constant pulse of its freshness, lineage, metadata, volume, distribution and value. Data observability, along with the effective implementation of monitoring and alerting, can enable organisations to identify and recover from unplanned outages due to data quality issues and also increase adoption of data products across the organisation.
Data observability is not achieved through the adoption of a single process or tool but a combination of different practices. The below figure shows how data observability relies on some key data disciplines which further depends on implementing supporting processes.
If you want to discuss how these data disciplines work together and how their prioritization enables effective data observability, please get in touch.
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