acryldata/datahub
Nov 2024 – Oct 2025
8 Months active
Languages Used
GradleJavaPythonYAMLJinjaGraphQLJavaScriptMarkdown
Technical Skills
API DesignAvroBackend DevelopmentBuild AutomationData ModelingDataHub Metadata
Shirshanka Das
PROFILE
Shirshanka Das
Shirshanka worked on the acrylidata/datahub repository, delivering features and fixes that advanced data governance, developer experience, and platform integration. Over eight months, he built and enhanced metadata modeling, lineage tracking, and cross-language utilities, using Java, Python, and TypeScript. His work included developing schema translation tools, CLI commands for GraphQL, and SDK improvements for structured property management. He stabilized CI pipelines and end-to-end tests with Cypress, improved documentation for Kafka integrations, and refreshed UI components for better usability. Shirshanka’s engineering approach emphasized robust validation, test coverage, and clear documentation, resulting in reliable workflows and improved onboarding for DataHub users.
Overall Statistics
Feature vs Bugs
65%Features
Repository Contributions
24Total
Bugs
7
Commits
24
Features
13
Lines of code
34,292
Activity Months8
Your Network
630 people
Work History
October 2025
3 Commits • 2 Features
Oct 1, 2025October 2025 monthly summary focusing on key accomplishments, business value delivery, and technical excellence for the acryldata/datahub repository.
3 Commits • 2 Features
Oct 1, 2025October 2025 monthly summary focusing on key accomplishments, business value delivery, and technical excellence for the acryldata/datahub repository.
October 2025
August 2025
1 Commits
Aug 1, 2025Month 2025-08 monthly summary for acryldata/datahub focusing on Cypress test stabilization for incidentsV2 and settingsV2. Stabilized smoke-test suites by refactoring tests to replace fixed cy.wait() with conditional waits, improving reliability and CI feedback. The change reduces flakiness and maintenance overhead, enabling faster release cycles.
August 2025
1 Commits
Aug 1, 2025Month 2025-08 monthly summary for acryldata/datahub focusing on Cypress test stabilization for incidentsV2 and settingsV2. Stabilized smoke-test suites by refactoring tests to replace fixed cy.wait() with conditional waits, improving reliability and CI feedback. The change reduces flakiness and maintenance overhead, enabling faster release cycles.
June 2025
2 Commits • 2 Features
Jun 1, 2025June 2025 – acrylidata/datahub: Focused on developer experience, governance, and documentation to accelerate Kafka Event Source integrations and strengthen certification clarity. Key features delivered include: (1) Kafka Event Source Schema Registry Configuration Documentation: Added documentation with examples for configuring the schema registry (default, external, and AWS Glue registries) to help users integrate Kafka events into DataHub. Commits: e827fdfebc45a1b1ee88b9d1f190f7eee804e5a4 (docs(actions): schema registry configuration tips (#13789)). (2) Preset Connector Certification Status Update: Updated the Preset connector certification status from TESTING to CERTIFIED to reflect improved validation and readiness; no functional code changes. Commits: 820a449b2ac1e31b0942e0fad1aa48e05022d61e (docs(ingestion): preset - update source certification status (#13641)). Major bugs fixed: none documented for this period. Overall impact: clearer guidance reduces onboarding time, lowers support load, and strengthens governance for data pipelines, enabling faster Kafka-based data ingestion into DataHub. Technologies/skills demonstrated: documentation best practices, schema registry concepts, Kafka event sources, AWS Glue registries, and release-note style communication.
2 Commits • 2 Features
Jun 1, 2025June 2025 – acrylidata/datahub: Focused on developer experience, governance, and documentation to accelerate Kafka Event Source integrations and strengthen certification clarity. Key features delivered include: (1) Kafka Event Source Schema Registry Configuration Documentation: Added documentation with examples for configuring the schema registry (default, external, and AWS Glue registries) to help users integrate Kafka events into DataHub. Commits: e827fdfebc45a1b1ee88b9d1f190f7eee804e5a4 (docs(actions): schema registry configuration tips (#13789)). (2) Preset Connector Certification Status Update: Updated the Preset connector certification status from TESTING to CERTIFIED to reflect improved validation and readiness; no functional code changes. Commits: 820a449b2ac1e31b0942e0fad1aa48e05022d61e (docs(ingestion): preset - update source certification status (#13641)). Major bugs fixed: none documented for this period. Overall impact: clearer guidance reduces onboarding time, lowers support load, and strengthens governance for data pipelines, enabling faster Kafka-based data ingestion into DataHub. Technologies/skills demonstrated: documentation best practices, schema registry concepts, Kafka event sources, AWS Glue registries, and release-note style communication.
June 2025
April 2025
4 Commits • 2 Features
Apr 1, 2025April 2025 (acryldata/datahub) focused on UX improvements, CI reliability, and code health. Key deliverables include the Announcement UI refresh with enhanced mobile UX (promoting MCP, improved search modal alignment, and refined announcement bar styling), a CI pipeline update to run smoke tests on Python 3.11 across steps for consistent testing, and a fix for a class name collision in MCP/MCL startup listeners by renaming to MCPApplicationStartupListener and MCLApplicationStartupListener. These changes collectively improve user engagement, accelerate feedback loops, and reduce startup/runtime risks.
April 2025
4 Commits • 2 Features
Apr 1, 2025April 2025 (acryldata/datahub) focused on UX improvements, CI reliability, and code health. Key deliverables include the Announcement UI refresh with enhanced mobile UX (promoting MCP, improved search modal alignment, and refined announcement bar styling), a CI pipeline update to run smoke tests on Python 3.11 across steps for consistent testing, and a fix for a class name collision in MCP/MCL startup listeners by renaming to MCPApplicationStartupListener and MCLApplicationStartupListener. These changes collectively improve user engagement, accelerate feedback loops, and reduce startup/runtime risks.
March 2025
2 Commits • 1 Features
Mar 1, 2025March 2025 monthly summary: Delivered a metadata model enhancement introducing subTypes across entities to enable finer classification of data assets, strengthening governance and asset discoverability. Also improved documentation quality by correcting blog links to point to the DataHub Medium page, ensuring users access current content. These changes deliver business value by accelerating data discovery for data stewards, improving governance oversight, and reducing user friction when navigating docs. Technologies and skills demonstrated include data model evolution with subTypes, disciplined change management with conventional commits, and documentation hygiene across the docs site.
2 Commits • 1 Features
Mar 1, 2025March 2025 monthly summary: Delivered a metadata model enhancement introducing subTypes across entities to enable finer classification of data assets, strengthening governance and asset discoverability. Also improved documentation quality by correcting blog links to point to the DataHub Medium page, ensuring users access current content. These changes deliver business value by accelerating data discovery for data stewards, improving governance oversight, and reducing user friction when navigating docs. Technologies and skills demonstrated include data model evolution with subTypes, disciplined change management with conventional commits, and documentation hygiene across the docs site.
March 2025
January 2025
6 Commits • 3 Features
Jan 1, 2025January 2025: Focused on delivering data discovery, lineage, and platform integration capabilities in acryldata/datahub. Key features shipped include an SDK enhancement for listing structured properties, DataProcessInstance lineage support, and consolidated DataPlatformInstance integration, all backed by tests and UI/frontend improvements. These changes improve data governance, model/dataset traceability, and platform search consistency across APIs, UI, and GraphQL.
January 2025
6 Commits • 3 Features
Jan 1, 2025January 2025: Focused on delivering data discovery, lineage, and platform integration capabilities in acryldata/datahub. Key features shipped include an SDK enhancement for listing structured properties, DataProcessInstance lineage support, and consolidated DataPlatformInstance integration, all backed by tests and UI/frontend improvements. These changes improve data governance, model/dataset traceability, and platform search consistency across APIs, UI, and GraphQL.
December 2024
3 Commits • 2 Features
Dec 1, 2024December 2024 Monthly Summary: Delivered cross-language URN utilities for DataHub, integrated Hudi as a supported data platform, and fixed critical timestamp handling in DataJobPatchBuilder to prevent client breakage. These changes improve test reliability, expand platform coverage, and safeguard data lineage across Java and Python SDKs, delivering measurable business value through more accurate data cataloging and platform interoperability.
3 Commits • 2 Features
Dec 1, 2024December 2024 Monthly Summary: Delivered cross-language URN utilities for DataHub, integrated Hudi as a supported data platform, and fixed critical timestamp handling in DataJobPatchBuilder to prevent client breakage. These changes improve test reliability, expand platform coverage, and safeguard data lineage across Java and Python SDKs, delivering measurable business value through more accurate data cataloging and platform interoperability.
December 2024
November 2024
3 Commits • 1 Features
Nov 1, 2024November 2024 focused on strengthening data integrity, enabling Java-based schema translation, and stabilizing core metadata workflows in acrylidata/datahub. Delivered Avro schema translation capabilities to DataHub metadata with library and CLI modules, enhanced tests, and validation utilities; fixed critical validation and patching issues to ensure reliable metadata updates. These efforts improve data governance accuracy, enable schema-driven metadata generation, and tighten patch construction for custom properties and aspects.
November 2024
3 Commits • 1 Features
Nov 1, 2024November 2024 focused on strengthening data integrity, enabling Java-based schema translation, and stabilizing core metadata workflows in acrylidata/datahub. Delivered Avro schema translation capabilities to DataHub metadata with library and CLI modules, enhanced tests, and validation utilities; fixed critical validation and patching issues to ensure reliable metadata updates. These efforts improve data governance accuracy, enable schema-driven metadata generation, and tighten patch construction for custom properties and aspects.
Activity
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Quality Metrics
Correctness94.2%
Maintainability91.8%
Architecture88.8%
Performance85.8%
AI Usage20.8%
Skills & Technologies
Programming Languages
CSSGradleGraphQLJavaJavaScriptJinjaMarkdownPegasusPythonShell
Technical Skills
API DesignAPI DevelopmentAPI RefactoringAvroBackend DevelopmentBuild AutomationCI/CDCLI DevelopmentCSSConfiguration ManagementCypressData LineageData ModelingDataHub MetadataDocumentation
Repositories Contributed To
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