Planning-Inspectorate/odw-synapse-workspace
Jul 2025 – Oct 2025
3 Months active
Languages Used
PythonSQLYAMLMarkdownMermaid
Technical Skills
Azure SynapseCloud Computing (Azure Synapse)Data EngineeringData ProcessingETLLogging
RohitShuklaPINS
PROFILE
Rohitshuklapins
Rohit Shukla developed and maintained robust data engineering workflows in the Planning-Inspectorate/odw-synapse-workspace repository, focusing on standardizing and curating large-scale datasets for analytics. He designed and updated Jupyter notebooks to transform raw data into standardized formats, implemented end-to-end data pipelines using Python and SQL, and integrated observability through enhanced logging and Azure Application Insights. Rohit also established foundational data models with ER diagrams, improved data traceability, and maintained pipeline reliability by addressing deployment issues. His work demonstrated depth in data modeling, ETL, and cloud monitoring, resulting in reproducible, scalable pipelines and higher data quality across multiple business domains.
Overall Statistics
Feature vs Bugs
98%Features
Repository Contributions
213Total
Bugs
2
Commits
213
Features
106
Lines of code
25,658
Activity Months3
Your Network
53 peopleSame Organization
@planninginspectorate.gov.uk40
Work History
October 2025
31 Commits • 15 Features
Oct 1, 2025October 2025 – Planning-Inspectorate/odw-synapse-workspace: Delivered foundational data modeling with ER diagrams and initial data model files; advanced data standardisation workflows via notebooks for listed buildings (including Rohit variant) and cleanup of obsolete components; expanded observability through Application Insights integration across notebooks; broad notebook maintenance to standardise data flows (raw_to_std, entraid, horizon harmonised docs). These efforts establish a scalable data model, reproducible pipelines, and improved monitoring, enabling faster analytics and higher data quality.
31 Commits • 15 Features
Oct 1, 2025October 2025 – Planning-Inspectorate/odw-synapse-workspace: Delivered foundational data modeling with ER diagrams and initial data model files; advanced data standardisation workflows via notebooks for listed buildings (including Rohit variant) and cleanup of obsolete components; expanded observability through Application Insights integration across notebooks; broad notebook maintenance to standardise data flows (raw_to_std, entraid, horizon harmonised docs). These efforts establish a scalable data model, reproducible pipelines, and improved monitoring, enabling faster analytics and higher data quality.
October 2025
August 2025
169 Commits • 89 Features
Aug 1, 2025August 2025 monthly summary for odw-synapse-workspace: Delivered extensive notebook updates across NSIP and Appeals domains, improved data standardization and traceability, and strengthened data curation pipelines. Focused on delivering concrete business value by standardizing raw data, enhancing logging, and improving insights throughput.
August 2025
169 Commits • 89 Features
Aug 1, 2025August 2025 monthly summary for odw-synapse-workspace: Delivered extensive notebook updates across NSIP and Appeals domains, improved data standardization and traceability, and strengthened data curation pipelines. Focused on delivering concrete business value by standardizing raw data, enhancing logging, and improving insights throughput.
July 2025
13 Commits • 2 Features
Jul 1, 2025July 2025 monthly summary for Planning-Inspectorate/odw-synapse-workspace focusing on delivering robust data transformation, observability, and pipeline reliability to improve data quality and operational efficiency. Key features delivered include Py_SB Raw to Standard Data Transformation and Observability Enhancements with added logging and pipeline integration, and Logging Utilities Enhancements Across Notebooks for unified diagnostics. Major bug fix: Deployment/Pipeline Configuration Reverts and SAP HR Data Trigger Fix to stabilize daily processing. Overall impact: improved data quality, end-to-end traceability, reduced toil, and safer deployments. Technologies/skills demonstrated include Python data pipelines, notebook-based ETL, logging/observability engineering, environment management, and DevOps practices.
13 Commits • 2 Features
Jul 1, 2025July 2025 monthly summary for Planning-Inspectorate/odw-synapse-workspace focusing on delivering robust data transformation, observability, and pipeline reliability to improve data quality and operational efficiency. Key features delivered include Py_SB Raw to Standard Data Transformation and Observability Enhancements with added logging and pipeline integration, and Logging Utilities Enhancements Across Notebooks for unified diagnostics. Major bug fix: Deployment/Pipeline Configuration Reverts and SAP HR Data Trigger Fix to stabilize daily processing. Overall impact: improved data quality, end-to-end traceability, reduced toil, and safer deployments. Technologies/skills demonstrated include Python data pipelines, notebook-based ETL, logging/observability engineering, environment management, and DevOps practices.
July 2025
Activity
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Quality Metrics
Correctness62.2%
Maintainability62.2%
Architecture61.4%
Performance61.4%
AI Usage22.8%
Skills & Technologies
Programming Languages
MarkdownMermaidPythonSQLYAML
Technical Skills
API IntegrationAzure SynapseCloud Computing (Azure Synapse)Cloud MonitoringCloud ServicesCode CleanupData AnalysisData CurationData EngineeringData LoadingData ModelingData ProcessingData StandardizationData TransformationDatabase Design
Repositories Contributed To
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