People Analytics

GitLab People Analytics Team Handbook Page

Overview

People Analytics uses data-driven insights to improve talent decisions and workforce processes at GitLab. We’re part of the People Strategy team, helping inform People Group decisions at all organizational levels through reporting, data solutions, and statistical analysis.

People Analytics Team Members

What We Do

Our Mission: Provide data insights to inform People decisions across GitLab by collecting and analyzing organizational, people, and talent data to improve business outcomes.

Key Objectives:

Reporting Solutions - Work with stakeholders to develop automated reporting solutions that deliver relevant People metrics efficently and accurately
Data Solutions - Collaborate with the Data Team to build scalable data models to support reporting and analytics
Analytical Solutions - Apply advanced statistical techniques (clustering, regression, survival analysis) to generate actionable insights and data-informed decisions for People Group and leadership throughout GitLab

Tools & Resources

Primary Tools

Tableau - Data visualization, dashboards, and ad-hoc analysis
RStudio/R - Statistical modeling and data cleaning. Learn more in our Rstudio handbook page
Snowflake - Data warehouse and SQL exploration
Culture Amp - Employee surveys and assessments
Google Sheets - Stakeholder-specific solutions when needed

People Analytics Handbook Contents

People Analytics Data Guide - Data models and metric definitions
People Data Governance - Data quality and compliance
People Analytics Tableau Dashboard Overview - Common dashboards and usage
People Analytics Survey Support - Culture Amp survey administration

External Resources

Wharton People Analytics - Annual conference and research
AIHR People Analytics - HR and analytics resources
HR Predictive Analytics - Textbook with practical examples
Google re:Work - Introductory resources
Handbook of Regression Modeling in People Analytics - Keith McNulty’s open-source book of regression modeling with examples in R and Python
Handbook of Graphs and Networks in People Analytics - Keith McNulty’s open-source book for Organizational Network Analysis
The Fundamentals of People Analytics - Craig Starbuck’s open-source book with examples of statistical analyses commonly used by People Analytics teams with examples in R

Data Governance & Security

GitLab’s commitment to transparency and efficiency extends to our data governance framework. The People Analytics team collaborates closely with People and Legal teams to ensure we only access data we are authorized to use. Our process includes access verification and stakeholder approval for all data requests, maintaining strict compliance with applicable laws and regulations.

Core Governance Principles:

Source System Priority - People Group daily operations remain in ther source systems to maintain data integrity and workflow efficiency
Strategic Data Warehousing - Our data warehouse, built on technologies like dbt and Snowflake is reserved for “up and out” organizational reporting and analytics
Data Minimization - We only bring in the data needed in reporting and anonymize information whenever possible to protect individual privacy
Comprehensive Tracking - We track data from source system to all downstream systems to understand and mitigate risk throughout the data lifecycle

This governance framework ensures that data remains consistent, reliable, and easy to work with while protecting sensitive information. For detailed information about our data governance processes, see our Data Governance handbook page.

Working With Us

Submit requests and ideas using issue templates in the People Analytics project.

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