mozilla/looker-spoke-default
Jan 2025 – Aug 2025
3 Months active
Languages Used
LookMLSQL
Technical Skills
Business IntelligenceData AnalysisData ModelingETLSQLData Engineering
Brad Ochocki
PROFILE
Brad Ochocki
During a three-month period, Brian Ochocki developed and maintained data forecasting features for the mozilla/looker-spoke-default repository. He built a Looker-derived table and Explore for Browser KPI Forecasts 2025, enabling product teams to analyze daily active users with a 28-day moving average. Using LookML and SQL, Brian enhanced the data model to support time-series forecasting and fixed a join bug to improve data reliability. He also addressed data quality by correcting mobile app classification and implemented a leap-year exclusion in date calculations, ensuring forecast accuracy. His work demonstrated depth in business intelligence, data modeling, and ETL engineering practices.
Overall Statistics
Feature vs Bugs
33%Features
Repository Contributions
4Total
Bugs
2
Commits
4
Features
1
Lines of code
166
Activity Months3
Your Network
403 peopleSame Organization
@mozilla.com364
Work History
August 2025
1 Commits
Aug 1, 2025August 2025 — Monthly summary for mozilla/looker-spoke-default: Focused on stabilizing KPI forecast calculations and data accuracy. Delivered a critical leap-year fix in the in-browser date-range logic to exclude February 29, 2024 from 2025 KPI forecasts, preventing an extra day from skewing results. This change preserves forecast integrity and trust in KPI dashboards.
1 Commits
Aug 1, 2025August 2025 — Monthly summary for mozilla/looker-spoke-default: Focused on stabilizing KPI forecast calculations and data accuracy. Delivered a critical leap-year fix in the in-browser date-range logic to exclude February 29, 2024 from 2025 KPI forecasts, preventing an extra day from skewing results. This change preserves forecast integrity and trust in KPI dashboards.
August 2025
July 2025
1 Commits
Jul 1, 2025Concise monthly summary for 2025-07 focusing on data quality improvements in KPI forecasting for the mozilla/looker-spoke-default repository. Delivered a critical bug fix to ensure correct mobile app classification in KPI forecasts, enhancing reporting accuracy and business insights. No new features shipped this month; primary effort centered on correcting data categorization for mobile products ('focus_android' and 'focus_ios').
July 2025
1 Commits
Jul 1, 2025Concise monthly summary for 2025-07 focusing on data quality improvements in KPI forecasting for the mozilla/looker-spoke-default repository. Delivered a critical bug fix to ensure correct mobile app classification in KPI forecasts, enhancing reporting accuracy and business insights. No new features shipped this month; primary effort centered on correcting data categorization for mobile products ('focus_android' and 'focus_ios').
January 2025
2 Commits • 1 Features
Jan 1, 2025January 2025 performance summary for mozilla/looker-spoke-default: Delivered the Browser KPI Forecasts 2025 Looker view and Explore, enabling product teams to analyze current and forecasted daily active users via a 28-day moving average. The Looker surface includes fields for product, forecast name, and date, supporting time-series forecasting workflows and more reliable decision-making. Fixed a join bug to ensure accurate data relationships in the derived table model, improving reporting reliability and reducing potential misinterpretation of forecast metrics. This work strengthens data-driven forecasting capabilities for 2025 and establishes a solid foundation for ongoing analytics delivery.
2 Commits • 1 Features
Jan 1, 2025January 2025 performance summary for mozilla/looker-spoke-default: Delivered the Browser KPI Forecasts 2025 Looker view and Explore, enabling product teams to analyze current and forecasted daily active users via a 28-day moving average. The Looker surface includes fields for product, forecast name, and date, supporting time-series forecasting workflows and more reliable decision-making. Fixed a join bug to ensure accurate data relationships in the derived table model, improving reporting reliability and reducing potential misinterpretation of forecast metrics. This work strengthens data-driven forecasting capabilities for 2025 and establishes a solid foundation for ongoing analytics delivery.
January 2025
Activity
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Quality Metrics
Correctness90.0%
Maintainability95.0%
Architecture95.0%
Performance85.0%
AI Usage20.0%
Skills & Technologies
Programming Languages
LookMLSQL
Technical Skills
Business IntelligenceData AnalysisData EngineeringData ModelingETLSQL
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