prefeitura-rio/queries-rj-iplanrio
Jul 2025 – Mar 2026
4 Months active
Languages Used
JinjaSQLYAML
Technical Skills
BigQueryCloud Cost ManagementCloud Data WarehousingData EngineeringData ModelingData Warehousing
Stella Costa
PROFILE
Stella Costa
Stella Maryane developed and enhanced cloud cost analytics and data warehousing solutions for the prefeitura-rio/queries-rj-iplanrio repository over four months. She built incremental BigQuery and GCP billing models, implemented cost-tracking pipelines, and improved data validation and reporting accuracy using SQL, dbt, and YAML configuration. Stella modernized data sources, refactored dashboard structures, and introduced monthly aggregation for storage costs, enabling more reliable budgeting and forecasting. Her work included cleaning legacy configurations, expanding test coverage, and streamlining repository organization. These efforts resulted in robust, maintainable data pipelines and dashboards that support scalable cost governance and operational decision-making for the organization.
Overall Statistics
Feature vs Bugs
83%Features
Repository Contributions
32Total
Bugs
2
Commits
32
Features
10
Lines of code
6,714
Activity Months4
Your Network
13 peopleShared Repositories
13
Arnaldo LimaMember
Bruno AlmeidaMember
Bruno MesquitaMember
d116626Member
Geraldo MaiaMember
GeraldoSilvaMaiaJuniorMember
GeraldoSilvaMaiaJuniorMember
Joao Pedro OliveiraMember
Luciano MunizMember
Work History
March 2026
7 Commits • 2 Features
Mar 1, 2026March 2026: Implemented key cost-visibility improvements in prefeitura-rio/queries-rj-iplanrio. Delivered GCP Cost Model Enhancements with separated credits and savings (new fields for CUD, other credits, and negotiated savings), updated YAML descriptions, and data validation to ensure reliable BRL reporting. Rolled out BigQuery Storage Cost Aggregation by Organization with monthly granularity, refined LAG logic, and latest-snapshot filtering for accurate organization-level cost insights. Strengthened data integrity with COALESCE-based calculations and line-level validations, and simplified config by removing schema/alias dependencies. These changes improve budgeting accuracy, forecasting, and cost optimization opportunities.
7 Commits • 2 Features
Mar 1, 2026March 2026: Implemented key cost-visibility improvements in prefeitura-rio/queries-rj-iplanrio. Delivered GCP Cost Model Enhancements with separated credits and savings (new fields for CUD, other credits, and negotiated savings), updated YAML descriptions, and data validation to ensure reliable BRL reporting. Rolled out BigQuery Storage Cost Aggregation by Organization with monthly granularity, refined LAG logic, and latest-snapshot filtering for accurate organization-level cost insights. Strengthened data integrity with COALESCE-based calculations and line-level validations, and simplified config by removing schema/alias dependencies. These changes improve budgeting accuracy, forecasting, and cost optimization opportunities.
March 2026
February 2026
17 Commits • 3 Features
Feb 1, 2026February 2026: Delivered essential data platform enhancements across billing, cost analytics, and student frequency analytics. Removed legacy billing references, modernized data sources, and strengthened cost visibility with BigQuery models and dashboards. Expanded testing and refactoring to improve reliability, maintainability, and operational efficiency, enabling better budgeting and decision-making.
February 2026
17 Commits • 3 Features
Feb 1, 2026February 2026: Delivered essential data platform enhancements across billing, cost analytics, and student frequency analytics. Removed legacy billing references, modernized data sources, and strengthened cost visibility with BigQuery models and dashboards. Expanded testing and refactoring to improve reliability, maintainability, and operational efficiency, enabling better budgeting and decision-making.
January 2026
4 Commits • 3 Features
Jan 1, 2026January 2026 monthly summary for prefeitura-rio/queries-rj-iplanrio: Focused on delivering value through improved cost visibility, robust CI readiness signals, and cleaner DBT project organization, while stabilizing the data pipeline. The work aligns with governance on cost modeling, deployment readiness, and model hygiene, enabling incremental billing data materialization and faster, more reliable insights.
4 Commits • 3 Features
Jan 1, 2026January 2026 monthly summary for prefeitura-rio/queries-rj-iplanrio: Focused on delivering value through improved cost visibility, robust CI readiness signals, and cleaner DBT project organization, while stabilizing the data pipeline. The work aligns with governance on cost modeling, deployment readiness, and model hygiene, enabling incremental billing data materialization and faster, more reliable insights.
January 2026
July 2025
4 Commits • 2 Features
Jul 1, 2025July 2025 monthly summary for prefeitura-rio/queries-rj-iplanrio focusing on delivering business value through cost visibility, data quality, and streamlined operations. The month centered on implementing cost-tracking capabilities, hardening data processing pipelines, and improving repository hygiene to support scalable cost analytics and governance.
July 2025
4 Commits • 2 Features
Jul 1, 2025July 2025 monthly summary for prefeitura-rio/queries-rj-iplanrio focusing on delivering business value through cost visibility, data quality, and streamlined operations. The month centered on implementing cost-tracking capabilities, hardening data processing pipelines, and improving repository hygiene to support scalable cost analytics and governance.
Activity
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Quality Metrics
Correctness89.0%
Maintainability85.2%
Architecture86.0%
Performance84.4%
AI Usage23.2%
Skills & Technologies
Programming Languages
JinjaSQLYAML
Technical Skills
BigQueryCloud Cost ManagementCloud Data WarehousingData EngineeringData ModelingData WarehousingETLGCPGCP BillingSQLSQL queriesSQL queryingYAMLYAML configurationdashboard development
Repositories Contributed To
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