snowplow/documentation
Apr 2025 – Jan 2026
4 Months active
Languages Used
MarkdownSQL
Technical Skills
DocumentationSQLdata recoverydata warehousingdocumentation
Jordan Peck
PROFILE
Jordan Peck
Jordan Peck contributed to the snowplow/documentation repository by delivering four targeted documentation features over four months, focusing on data recovery, warehousing, and analytics clarity. Jordan authored comprehensive guides for recovering failed events using SQL, providing workflows and examples for BigQuery, Snowflake, and Databricks, and clarified event inclusion criteria to improve onboarding and analytics reliability. The work emphasized precise, business-focused guidance, cross-warehouse compatibility, and data integrity validation, with careful attention to traceability and issue alignment. Using SQL and Markdown, Jordan’s contributions deepened the repository’s technical accuracy and usability, addressing real-world data challenges without introducing new bugs or regressions.
Overall Statistics
Feature vs Bugs
100%Features
Repository Contributions
4Total
Bugs
0
Commits
4
Features
4
Lines of code
727
Activity Months4
Your Network
34 peopleWork History
January 2026
1 Commits • 1 Features
Jan 1, 2026January 2026 monthly summary for the Snowplow documentation work stream, focusing on delivering precise, business-focused guidance for recovering failed events in Databricks SQL and improving cross-warehouse clarity.
1 Commits • 1 Features
Jan 1, 2026January 2026 monthly summary for the Snowplow documentation work stream, focusing on delivering precise, business-focused guidance for recovering failed events in Databricks SQL and improving cross-warehouse clarity.
January 2026
November 2025
1 Commits • 1 Features
Nov 1, 2025November 2025: Delivered a comprehensive Event Recovery Guide for Failed Events in the snowplow/documentation repo. The guide provides a SQL-based workflow to identify failure types, reconstruct data, and reinsert failed events into the main events table, with practical BigQuery and Snowflake examples to assist users in recovering event data.
November 2025
1 Commits • 1 Features
Nov 1, 2025November 2025: Delivered a comprehensive Event Recovery Guide for Failed Events in the snowplow/documentation repo. The guide provides a SQL-based workflow to identify failure types, reconstruct data, and reinsert failed events into the main events table, with practical BigQuery and Snowflake examples to assist users in recovering event data.
August 2025
1 Commits • 1 Features
Aug 1, 2025In August 2025, delivered a targeted documentation improvement for snowplow/documentation by clarifying the dbt Passthrough Field Derivation. The change fixes a typo and specifies which event a field is derived from within derived tables, enhancing accuracy for data modeling. Implemented as a focused, single-commit change aligned with issue #1349, reinforcing governance and traceability in the repository.
1 Commits • 1 Features
Aug 1, 2025In August 2025, delivered a targeted documentation improvement for snowplow/documentation by clarifying the dbt Passthrough Field Derivation. The change fixes a typo and specifies which event a field is derived from within derived tables, enhancing accuracy for data modeling. Implemented as a focused, single-commit change aligned with issue #1349, reinforcing governance and traceability in the repository.
August 2025
April 2025
1 Commits • 1 Features
Apr 1, 2025April 2025 monthly summary for snowplow/documentation focused on delivering targeted documentation improvements that enhance data accuracy and user understanding. Key change this month clarifies that screen_view events are included in base_events_this_run for session analysis, improving transparency of event inclusion criteria and analytics reliability.
April 2025
1 Commits • 1 Features
Apr 1, 2025April 2025 monthly summary for snowplow/documentation focused on delivering targeted documentation improvements that enhance data accuracy and user understanding. Key change this month clarifies that screen_view events are included in base_events_this_run for session analysis, improving transparency of event inclusion criteria and analytics reliability.
Activity
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Quality Metrics
Correctness95.0%
Maintainability95.0%
Architecture95.0%
Performance95.0%
AI Usage20.0%
Skills & Technologies
Programming Languages
MarkdownSQL
Technical Skills
DocumentationSQLdata recoverydata warehousingdocumentation
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