Nike-Inc/spark-expectations
Sep 2025 – Sep 2025
1 Month active
Languages Used
PythonSQL
Technical Skills
Data EngineeringData QualityDelta LakeNotebook DevelopmentSpark
RishabGulati7
PROFILE
Rishabgulati7
Rishab Gulati developed an Aggregated Data Quality (agg_dq) Demo Notebook for the Nike-Inc/spark-expectations repository, focusing on end-to-end demonstration of data quality workflows. He designed the notebook to guide users through Spark setup, aggregation rule definition, and execution of data quality expectations on sample datasets, incorporating interactive widgets for configuration and verification. Using Python and SQL within a Delta Lake environment, Rishab ensured the notebook was reproducible by anchoring it to a specific commit, providing a reliable onboarding resource. This work emphasized clarity and reusability, enabling teams to validate and adopt agg_dq features efficiently while maintaining high data engineering standards.
Overall Statistics
Feature vs Bugs
100%Features
Repository Contributions
1Total
Bugs
0
Commits
1
Features
1
Lines of code
613
Activity Months1
Work History
September 2025
1 Commits • 1 Features
Sep 1, 2025September 2025 — Key deliverable: Aggregated Data Quality (agg_dq) Demo Notebook for spark-expectations. This end-to-end notebook demonstrates Spark setup, aggregation rule definitions, and execution of data quality expectations on sample data, with interactive widgets for configuration and verification. The work is anchored to commit a0a60f943de89518a94f793378ff33150f9de8bf, providing a reproducible reference for onboarding and validating agg_dq.
1 Commits • 1 Features
Sep 1, 2025September 2025 — Key deliverable: Aggregated Data Quality (agg_dq) Demo Notebook for spark-expectations. This end-to-end notebook demonstrates Spark setup, aggregation rule definitions, and execution of data quality expectations on sample data, with interactive widgets for configuration and verification. The work is anchored to commit a0a60f943de89518a94f793378ff33150f9de8bf, providing a reproducible reference for onboarding and validating agg_dq.
September 2025
Activity
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Quality Metrics
Correctness100.0%
Maintainability100.0%
Architecture100.0%
Performance100.0%
AI Usage20.0%
Skills & Technologies
Programming Languages
PythonSQL
Technical Skills
Data EngineeringData QualityDelta LakeNotebook DevelopmentSpark
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