edanalytics/earthmover_edfi_bundles
Oct 2025 – Oct 2025
1 Month active
Languages Used
CSVJSONPythonYAMLcsvjsonyaml
Technical Skills
Data EngineeringData ModelingData TransformationData ValidationETLEd-Fi Implementation
Bruk
PROFILE
Bruk
Developed and delivered Ed-Fi assessment data ingestion pipelines for KRA and myIGDIs within the edanalytics/earthmover_edfi_bundles repository, focusing on end-to-end data mapping and validation. Leveraged Python scripting and data transformation techniques to automate the ingestion process, including configuration files, templates, and seed data for accurate mapping of student IDs and assessment results. Introduced a pre-processing step for myIGDIs to enhance data formatting and processing performance. Comprehensive documentation and configuration were provided to support both Earthmover and Lightbeam, enabling streamlined ingestion and validation workflows. This work reduced manual data wrangling and improved the reliability of downstream analytics for education partners.
Overall Statistics
Feature vs Bugs
100%Features
Repository Contributions
2Total
Bugs
0
Commits
2
Features
1
Lines of code
1,435
Activity Months1
Your Network
9 peopleShared Repositories
9
Work History
October 2025
2 Commits • 1 Features
Oct 1, 2025October 2025 — Implemented and delivered Ed-Fi assessment data ingestion pipelines for KRA and myIGDIs within edanalytics/earthmover_edfi_bundles. The work provides end-to-end ingestion and mapping to the Ed-Fi data model, enabling automated validation and downstream analytics. The KRA pipeline includes configuration files, templates, and seed data to correctly map student IDs, performance levels, and assessments. MyIGDIs received a pre-processing step for data formatting, resulting in improved data quality and processing performance. Comprehensive documentation and configuration for Earthmover and Lightbeam, plus sample data, support easy ingestion and validation in staging/production. These changes reduce manual data wrangling, accelerate reporting cycles, and improve trust in analytics for education partners.
2 Commits • 1 Features
Oct 1, 2025October 2025 — Implemented and delivered Ed-Fi assessment data ingestion pipelines for KRA and myIGDIs within edanalytics/earthmover_edfi_bundles. The work provides end-to-end ingestion and mapping to the Ed-Fi data model, enabling automated validation and downstream analytics. The KRA pipeline includes configuration files, templates, and seed data to correctly map student IDs, performance levels, and assessments. MyIGDIs received a pre-processing step for data formatting, resulting in improved data quality and processing performance. Comprehensive documentation and configuration for Earthmover and Lightbeam, plus sample data, support easy ingestion and validation in staging/production. These changes reduce manual data wrangling, accelerate reporting cycles, and improve trust in analytics for education partners.
October 2025
Activity
Loading activity data...
Quality Metrics
Correctness90.0%
Maintainability80.0%
Architecture90.0%
Performance80.0%
AI Usage20.0%
Skills & Technologies
Programming Languages
CSVJSONPythonYAMLcsvjsonyaml
Technical Skills
Data EngineeringData ModelingData TransformationData ValidationETLEd-Fi ImplementationEd-Fi IntegrationScripting
Repositories Contributed To
Overview of all repositories you've contributed to across your timeline