Planning-Inspectorate/odw-synapse-workspace
Dec 2024 – Mar 2025
4 Months active
Languages Used
PythonSQLTerraformYAMLMarkdownBashJSON
Technical Skills
API DevelopmentAzure Data FactoryAzure FunctionsBackend DevelopmentCI/CDData Engineering
Kathryn Thompson
PROFILE
Kathryn Thompson
Kathryn Thompson contributed to the Planning-Inspectorate/odw-synapse-workspace repository by engineering robust data pipelines, APIs, and deployment processes over four months. She enhanced inspector data processing by introducing curated and raw data flows, standardized raw data transformation, and integrated new data structures using Python and Azure Synapse Analytics. Kathryn improved API reliability with Azure Functions, implemented unit testing with pytest, and strengthened CI/CD pipelines for faster, more deterministic feedback. Her work included auditing tools for notebook governance, documentation modernization, and resilient retry logic in Azure Data Factory. These efforts improved data quality, maintainability, onboarding efficiency, and operational reliability across the platform.
Overall Statistics
Feature vs Bugs
92%Features
Repository Contributions
23Total
Bugs
1
Commits
23
Features
11
Lines of code
3,510
Activity Months4
Your Network
16 peopleSame Organization
@valtech.com2
David MealoMember
Jon EkdahlMember
Work History
March 2025
7 Commits • 3 Features
Mar 1, 2025March 2025: Focused on reliability, efficiency, and governance in Planning-Inspectorate/odw-synapse-workspace. Key outcomes include faster, more deterministic tests via CI/CD pipeline improvements; increased resilience of data processing through Data Factory retry enhancements; and improved deployment/docs for Service Bus function apps and credential management, reducing onboarding time and credential risk. No critical bugs reported; the team delivered measurable business value in faster feedback, more reliable data tasks, and clearer deployment guidance.
7 Commits • 3 Features
Mar 1, 2025March 2025: Focused on reliability, efficiency, and governance in Planning-Inspectorate/odw-synapse-workspace. Key outcomes include faster, more deterministic tests via CI/CD pipeline improvements; increased resilience of data processing through Data Factory retry enhancements; and improved deployment/docs for Service Bus function apps and credential management, reducing onboarding time and credential risk. No critical bugs reported; the team delivered measurable business value in faster feedback, more reliable data tasks, and clearer deployment guidance.
March 2025
February 2025
4 Commits • 3 Features
Feb 1, 2025February 2025 Monthly Summary for Planning-Inspectorate/odw-synapse-workspace. This period focused on delivering reliable data standardization capabilities, ensuring DaRT readiness for version 6.0.1, and enhancing governance/observability of the Azure Synapse workspace to support maintainability, compliance, and cost control. Key outcomes include delivered features to standardize raw data into a robust standard format, guarantees that DaRT notebooks for 6.0.1 exist and are wired into the pipeline, and the introduction of audit tooling to map pipelines/notebooks and surface unreferenced/not-run components for accountability. Overall impact: Increased reliability and efficiency of data ingestion and governance processes, reduced onboarding risk for new data sources, and improved visibility into workspace utilization and execution status. Technologies/skills demonstrated: Python scripting, Jupyter notebooks, Azure Synapse Analytics, data transformation pipelines, notebook/pipeline governance, hands-on debugging and maintenance of production data tooling.
February 2025
4 Commits • 3 Features
Feb 1, 2025February 2025 Monthly Summary for Planning-Inspectorate/odw-synapse-workspace. This period focused on delivering reliable data standardization capabilities, ensuring DaRT readiness for version 6.0.1, and enhancing governance/observability of the Azure Synapse workspace to support maintainability, compliance, and cost control. Key outcomes include delivered features to standardize raw data into a robust standard format, guarantees that DaRT notebooks for 6.0.1 exist and are wired into the pipeline, and the introduction of audit tooling to map pipelines/notebooks and surface unreferenced/not-run components for accountability. Overall impact: Increased reliability and efficiency of data ingestion and governance processes, reduced onboarding risk for new data sources, and improved visibility into workspace utilization and execution status. Technologies/skills demonstrated: Python scripting, Jupyter notebooks, Azure Synapse Analytics, data transformation pipelines, notebook/pipeline governance, hands-on debugging and maintenance of production data tooling.
January 2025
3 Commits • 1 Features
Jan 1, 2025January 2025 monthly summary for Planning-Inspectorate/odw-synapse-workspace: Delivered two core improvements focused on long-term maintainability and reliability. Key features: codebase cleanup removing unused/superseded packages to reduce technical debt and Azure Function Apps documentation modernization for clearer onboarding and easier maintenance. Major bug fix: preserved the original JSON value on decode error in getDaRT, enabling easier debugging and potential data reprocessing. Impact: reduced maintenance burden, faster onboarding, improved data debugging, and more reliable operation. Technologies/skills demonstrated: Python, Azure Functions, code cleanup practices, documentation discipline, and robust debugging.
3 Commits • 1 Features
Jan 1, 2025January 2025 monthly summary for Planning-Inspectorate/odw-synapse-workspace: Delivered two core improvements focused on long-term maintainability and reliability. Key features: codebase cleanup removing unused/superseded packages to reduce technical debt and Azure Function Apps documentation modernization for clearer onboarding and easier maintenance. Major bug fix: preserved the original JSON value on decode error in getDaRT, enabling easier debugging and potential data reprocessing. Impact: reduced maintenance burden, faster onboarding, improved data debugging, and more reliable operation. Technologies/skills demonstrated: Python, Azure Functions, code cleanup practices, documentation discipline, and robust debugging.
January 2025
December 2024
9 Commits • 4 Features
Dec 1, 2024Month: 2024-12 | Repository: Planning-Inspectorate/odw-synapse-workspace. Delivered notable data engineering and deployment improvements including inspector data processing enhancements, GetDaRT API with unit tests, harmonised DB connection/config updates, and release pipeline refinements. These efforts improve data quality, accessibility of detailed appeal information, configuration consistency, and release stability, delivering measurable business value through faster data-driven decisions, reduced manual intervention, and more reliable deployments.
December 2024
9 Commits • 4 Features
Dec 1, 2024Month: 2024-12 | Repository: Planning-Inspectorate/odw-synapse-workspace. Delivered notable data engineering and deployment improvements including inspector data processing enhancements, GetDaRT API with unit tests, harmonised DB connection/config updates, and release pipeline refinements. These efforts improve data quality, accessibility of detailed appeal information, configuration consistency, and release stability, delivering measurable business value through faster data-driven decisions, reduced manual intervention, and more reliable deployments.
Activity
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Quality Metrics
Correctness83.4%
Maintainability86.0%
Architecture76.6%
Performance77.4%
AI Usage20.0%
Skills & Technologies
Programming Languages
BashJSONMarkdownPythonSQLTerraformYAML
Technical Skills
API DevelopmentAPI IntegrationAPI ManagementAzure Data FactoryAzure DevOpsAzure FunctionsAzure Key VaultAzure PipelinesAzure SynapseBackend DevelopmentCI/CDCode RefactoringData EngineeringData Pipeline DevelopmentData Pipeline Management
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