Mozilla Data Documentation
1.
Getting Started
1.1.
Terminology
1.2.
Gaining Access
1.3.
Analysis Quick Start
1.4.
Tools for Data Analysis
1.5.
Common Analysis Gotchas
1.6.
Choosing a Desktop Dataset
1.7.
Choosing a Mobile Dataset
1.8.
Getting Help
1.9.
Reporting a problem
2.
Metrics
2.1.
Definitions
2.1.1.
Metrics
2.1.2.
Usage Criteria
2.1.3.
Slicing Dimensions
2.2.
Metrics Standardization and Policy
3.
Tutorials & Cookbooks
3.1.
Analysis
3.1.1.
Accessing Public Data
3.1.2.
Accessing and working with BigQuery
3.1.2.1.
Access
3.1.2.2.
Writing Queries
3.1.2.3.
Optimization
3.1.2.4.
Custom analysis with Spark
3.1.3.
Introduction to STMO
3.1.4.
Accessing Glean data
3.1.5.
Dataset-Specific
3.1.5.1.
Working with Normandy events
3.1.5.2.
Working with Crash Pings
3.1.5.3.
Working with Bit Patterns in Clients Last Seen
3.1.5.4.
Visualizing Percentiles of an Main Ping Exponential Histogram
3.1.6.
Real-time
3.1.6.1.
Seeing Your Own Pings
3.1.7.
Metrics
3.1.7.1.
Daily Active Users (DAU and MAU)
3.1.7.2.
Active DAU (aDAU)
3.1.7.3.
Retention
3.2.
Operational
3.2.1.
Creating a Prototype Data Project on Google Cloud Platform
3.2.2.
Creating Static Dashboards with Protosaur
3.2.3.
Scheduling BigQuery Queries in Airflow
3.2.4.
Building and Deploying Containers to GCR with CircleCI
3.2.5.
Publishing Datasets
3.3.
Sending telemetry
3.3.1.
Implementing Experiments
3.3.2.
Sending Events
3.3.3.
Sending a Custom Ping
4.
Data Platform Reference
4.1.
Guiding Principles for Data Infrastructure
4.2.
Glean overview
4.3.
Overview of Mozilla's Data Pipeline
4.3.1.
HTTP Edge Server Specification
4.3.2.
Event Pipeline Detail
4.3.3.
Schemas
4.3.4.
Channel Normalization
4.3.5.
Sampling
4.4.
SQL Style Guide
4.5.
Telemetry Behavior Reference
4.5.1.
History of Telemetry
4.5.2.
Profile Behavior
4.5.2.1.
Profile Creation
4.5.2.2.
Real World Usage
4.5.2.3.
Profile History
4.5.3.
Engagement metrics
4.5.4.
User states/Segments
4.6.
Project Glossary
5.
Dataset Reference
5.1.
Pings
5.2.
Derived Datasets
5.2.1.
Active Profiles
5.2.2.
Addons
5.2.3.
Addons Daily
5.2.4.
Autonomous System Aggregates
5.2.5.
Attitudes Daily
5.2.6.
Clients Daily
5.2.7.
Clients Last Seen
5.2.8.
Events
5.2.9.
Exact MAU
5.2.10.
Main Summary
5.2.11.
Socorro Crash Reports
5.2.12.
SSL Ratios (public)
5.2.13.
Telemetry Aggregates
5.3.
Experiment Datasets
5.3.1.
Jetstream
5.3.2.
Accessing Heartbeat data
5.3.3.
Accessing Shield Study data
5.3.4.
Dynamic telemetry
5.4.
Search Datasets
5.4.1.
Search Aggregates
5.4.2.
Search Clients Daily
5.4.3.
Search Clients Last Seen
5.4.4.
Client LTV
5.5.
Non-Desktop Datasets
5.5.1.
Day 2-7 Activation
5.5.2.
Google Play Store
5.5.3.
Apple App Store
5.5.4.
Events Daily
5.6.
Other Datasets
5.6.1.
hgpush
5.6.2.
Stub installer ping
5.6.3.
Activity Stream
5.6.4.
bmobugs
5.7.
Firefox Accounts Datasets
5.7.1.
Firefox Account Attribution
5.7.2.
Firefox Account Funnel Metrics
5.7.3.
Firefox Account Email Metrics
5.8.
Static Datasets
5.8.1.
Normalized OS Names And Versions
6.
Historical Reference
6.1.
Previous AWS Pipeline Overview
6.2.
In-depth AWS Data Pipeline Detail
6.3.
Legacy Census Metrics
6.4.
Obsolete Datasets
6.4.1.
Churn
6.4.2.
Client Count
6.4.3.
Client Count Daily
6.4.4.
Crash Aggregates
6.4.5.
Crash Summary
6.4.6.
Error Aggregates
6.4.7.
First Shutdown Summary
6.4.8.
Heavy Users
6.4.9.
Longitudinal
6.4.10.
Retention
6.4.11.
Sync Summary
6.4.12.
Update
7.
Contributing
7.1.
Style Guide
7.2.
Structure
Light (default)
Rust
Coal
Navy
Ayu
Mozilla Data Documentation
Analysis
This section contains tutorials on how to analyze Telemetry data.