Reduce Data Engineer Service Requests by 80% with Self-Serve Access

Struggling with too many data requests overwhelming your engineers? Reduce Data Engineer Service Requests by 80% with Self-Serve Access
In this video, Prukalpa Sankar, co-founder of Atlan, explains how taking a data as a product approach and building self-serve data access can drastically reduce the service requests faced by data engineers.
She provides an example of a B2B ecommerce company that leveraged Atlan to build a data portal with automated metadata like data freshness, column lineage, and dbt tag-based metrics. By making data pipelines and their metadata reusable and reproducible through Atlan, this company was able to reduce slack messages for their data and analytics engineers by 80%.
Prukalpa explains that by bringing context like Airflow SLAs, freshness, lineage, and more directly into self-serve data access, data teams can offload repetitive questions and empower business teams with the knowledge they need. The video provides a compelling example of how data as a product with rich, automated metadata can optimize data teams and unlock organizational productivity.
Atlan - The Only Data Catalog That Activates Your Metadata
Atlan is the leading active metadata platform for modern data teams. It creates a single source of truth by acting as a collaborative workspace for data teams and bringing context back into the tools where data teams live. Atlan features deep integrations across the modern data stack, including Slack, Snowflake, dbt Labs, Fivetran, Redshift, Looker, and Tableau. A pioneer in the space, Atlan was named a Leader in the Forrester Wave™: Enterprise Data Catalogs for DataOps and was recognized by Gartner seven times in 2021.
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