
Miriam Canones enhanced the dagster-io/dagster repository by improving the Tableau integration’s data lineage and robustness. She developed a feature to retain hidden Tableau sheets for internal lineage tracking, ensuring data governance while excluding them from external asset definitions. Addressing reliability, Miriam resolved a KeyError in dependency lookups by validating data source and sheet IDs before access, and improved error handling by allowing the system to skip and log failing Tableau workbooks rather than halting the entire fetch process. Her work leveraged Python for backend development, data integration, and comprehensive unit testing, demonstrating thoughtful attention to resilience and observability.
Month: 2025-12 — Quarterly/Monthly performance summary for the Dagster repo focusing on the Tableau integration. Delivered targeted fixes and a key feature to improve data lineage while enhancing resilience and observability. Highlights include robust dependency handling and partial-failure tolerance in Tableau fetches, and retention of hidden sheets for internal lineage with appropriate data governance.
Month: 2025-12 — Quarterly/Monthly performance summary for the Dagster repo focusing on the Tableau integration. Delivered targeted fixes and a key feature to improve data lineage while enhancing resilience and observability. Highlights include robust dependency handling and partial-failure tolerance in Tableau fetches, and retention of hidden sheets for internal lineage with appropriate data governance.

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