
Rupali Kishore enhanced the atlanhq/atlan-python and atlanhq/atlan-java repositories by building robust support for Dataverse and CustomEntity asset types, enabling Atlan to recognize and manage these as distinct data sources. She implemented creator methods, generator templates, and comprehensive integration tests using Python and Java, focusing on API design, backend development, and data modeling. Her work included explicit ADLS asset naming, code cleanup, and formatting improvements to increase maintainability and reliability. By expanding asset management capabilities and enforcing code quality standards, Rupali improved developer experience, streamlined onboarding, and strengthened data governance across Atlan’s SDKs and connector workflows.

February 2025 monthly summary for atlanhq/atlan-python highlighting business value and technical achievements: delivered explicit ADLS naming support, expanded model attributes, and strengthened code quality with targeted formatting improvements. These changes enable precise storage tagging for ADLS assets, improve governance traceability, and increase maintainability for the assets module.
February 2025 monthly summary for atlanhq/atlan-python highlighting business value and technical achievements: delivered explicit ADLS naming support, expanded model attributes, and strengthened code quality with targeted formatting improvements. These changes enable precise storage tagging for ADLS assets, improve governance traceability, and increase maintainability for the assets module.
January 2025 performance summary: Delivered cross-language Dataverse asset capabilities and CustomEntity asset types for both Python and Java SDKs, with strong test coverage and focused code quality improvements. In atlan-python, shipped Dataverse Asset Creation and Management and Custom Entity Support with generator templates and comprehensive unit/integration tests, complemented by cleanup efforts to remove dead code and enforce style consistency via Black. In atlan-java, introduced Dataverse assets support and CustomEntity asset type, accompanied by integration tests and updated connector configurations to recognize Dataverse as a distinct connector type, plus overall code quality and documentation improvements (spotless formatting and interface text tweaks). Overall, these deliverables enable programmatic asset provisioning and management, improve developer experience, and increase reliability and maintainability across SDKs, driving faster onboarding and clearer asset governance.
January 2025 performance summary: Delivered cross-language Dataverse asset capabilities and CustomEntity asset types for both Python and Java SDKs, with strong test coverage and focused code quality improvements. In atlan-python, shipped Dataverse Asset Creation and Management and Custom Entity Support with generator templates and comprehensive unit/integration tests, complemented by cleanup efforts to remove dead code and enforce style consistency via Black. In atlan-java, introduced Dataverse assets support and CustomEntity asset type, accompanied by integration tests and updated connector configurations to recognize Dataverse as a distinct connector type, plus overall code quality and documentation improvements (spotless formatting and interface text tweaks). Overall, these deliverables enable programmatic asset provisioning and management, improve developer experience, and increase reliability and maintainability across SDKs, driving faster onboarding and clearer asset governance.
December 2024 – Focused on expanding connectivity by introducing Dataverse as a first-class connector in the Python SDK. Delivered Dataverse Connector Support, enabling Atlan to recognize and process Dataverse as a distinct data source within the existing connector/workflow framework. This work lays the foundation for cross-source data workflows and expands data source coverage for customers using Dataverse, driving improved data discovery and lineage.
December 2024 – Focused on expanding connectivity by introducing Dataverse as a first-class connector in the Python SDK. Delivered Dataverse Connector Support, enabling Atlan to recognize and process Dataverse as a distinct data source within the existing connector/workflow framework. This work lays the foundation for cross-source data workflows and expands data source coverage for customers using Dataverse, driving improved data discovery and lineage.
Overview of all repositories you've contributed to across your timeline