mozilla/looker-spoke-default
Feb 2025 – Oct 2025
4 Months active
Languages Used
LookMLSQL
Technical Skills
Dashboard ConfigurationDashboard DevelopmentDashboardingData AnalysisData FilteringData Visualization
Mike Williams
PROFILE
Mike Williams
Over four months, contributed to the mozilla/looker-spoke-default repository by building and refining business intelligence dashboards focused on experiment enrollments and user preference changes. Leveraging LookML and SQL, developed features such as sampling-based approximations for unenrollment counts, unified tracking of user preference changes, and dynamic dashboard date filtering. Enhanced data modeling and visualization to improve measurement accuracy and cross-dashboard consistency, while targeted bug fixes increased reliability in error analytics. The work included refactoring dashboards to use Glean events for finer data granularity, consolidating metrics, and standardizing event schemas, supporting data-driven decision-making for product and analytics teams across multiple releases.
Overall Statistics
Feature vs Bugs
83%Features
Repository Contributions
9Total
Bugs
1
Commits
9
Features
5
Lines of code
2,119
Activity Months4
Your Network
416 peopleSame Organization
@mozilla.com376
Work History
October 2025
2 Commits • 1 Features
Oct 1, 2025October 2025 monthly summary for mozilla/looker-spoke-default. Focused on delivering a unified capability to track user preference changes (changed_pref) across experiments and enrollments dashboards, with an emphasis on business value and data-driven insights.
2 Commits • 1 Features
Oct 1, 2025October 2025 monthly summary for mozilla/looker-spoke-default. Focused on delivering a unified capability to track user preference changes (changed_pref) across experiments and enrollments dashboards, with an emphasis on business value and data-driven insights.
October 2025
June 2025
2 Commits • 1 Features
Jun 1, 2025June 2025: Focused on delivering and stabilizing experiment enrollment analysis dashboards for mozilla/looker-spoke-default. Implemented initial Looker dashboard for enrollments and related metrics, followed by a Glean-based refactor that uses Glean events for consistency and finer data granularity. This work provided consolidated metrics, improved data governance, and faster insights into experiment performance. No major bugs reported; engineering cadence remained steady with validation of data pipelines. Key commits include 54201ee6523229eb9b5536d89889eb9eaebe5862 and af41be7f9ba41d74b7edfd8f844f86f9e6aef992.
June 2025
2 Commits • 1 Features
Jun 1, 2025June 2025: Focused on delivering and stabilizing experiment enrollment analysis dashboards for mozilla/looker-spoke-default. Implemented initial Looker dashboard for enrollments and related metrics, followed by a Glean-based refactor that uses Glean events for consistency and finer data granularity. This work provided consolidated metrics, improved data governance, and faster insights into experiment performance. No major bugs reported; engineering cadence remained steady with validation of data pipelines. Key commits include 54201ee6523229eb9b5536d89889eb9eaebe5862 and af41be7f9ba41d74b7edfd8f844f86f9e6aef992.
March 2025
2 Commits • 1 Features
Mar 1, 2025Month 2025-03 — Delivered dashboard date filter integration and labeling consistency for mozilla/looker-spoke-default. Key features: dashboards now dynamically follow the dashboard date filter by removing default timeframes; event count labeling across dashboards standardized, with 'Adjusted Event Count' for general charts and updated the calculated field label to 'Approximate Event Count' in the experiment enrollments dashboard. Fixed a regression where daily enrollments charts did not respect the dashboard date filter. Impact: improved data accuracy, cross-dashboard consistency, and faster, clearer decision-making for product and data teams. Technologies/skills: Looker dashboards, data visualization, label standardization, field renaming, and targeted refactoring.
2 Commits • 1 Features
Mar 1, 2025Month 2025-03 — Delivered dashboard date filter integration and labeling consistency for mozilla/looker-spoke-default. Key features: dashboards now dynamically follow the dashboard date filter by removing default timeframes; event count labeling across dashboards standardized, with 'Adjusted Event Count' for general charts and updated the calculated field label to 'Approximate Event Count' in the experiment enrollments dashboard. Fixed a regression where daily enrollments charts did not respect the dashboard date filter. Impact: improved data accuracy, cross-dashboard consistency, and faster, clearer decision-making for product and data teams. Technologies/skills: Looker dashboards, data visualization, label standardization, field renaming, and targeted refactoring.
March 2025
February 2025
3 Commits • 2 Features
Feb 1, 2025February 2025 monthly summary for mozilla/looker-spoke-default focusing on delivering business value through dashboard enhancements and metrics accuracy. Key work includes sampling-based enhancements to the Experiment enrollments dashboard, a dynamic 1% sampling-based approximation for unenrollment counts, and a bug fix to improve error analytics reliability by excluding EnrollmentNotCompleteException from the total error count. These changes enhance dashboard clarity, measurement accuracy, and decision-support signals for product analytics teams.
February 2025
3 Commits • 2 Features
Feb 1, 2025February 2025 monthly summary for mozilla/looker-spoke-default focusing on delivering business value through dashboard enhancements and metrics accuracy. Key work includes sampling-based enhancements to the Experiment enrollments dashboard, a dynamic 1% sampling-based approximation for unenrollment counts, and a bug fix to improve error analytics reliability by excluding EnrollmentNotCompleteException from the total error count. These changes enhance dashboard clarity, measurement accuracy, and decision-support signals for product analytics teams.
Activity
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Quality Metrics
Correctness90.0%
Maintainability91.2%
Architecture86.6%
Performance84.4%
AI Usage20.0%
Skills & Technologies
Programming Languages
LookMLSQL
Technical Skills
Business IntelligenceDashboard ConfigurationDashboard DevelopmentDashboardingData AnalysisData EngineeringData FilteringData ModelingData VisualizationExperimentation AnalysisLookMLLookerSQL
Repositories Contributed To
Overview of all repositories you've contributed to across your timeline