Data Subject Request API Version 1 and 2
Data Subject Request API Version 3
Platform API Overview
Accounts
Apps
Audiences
Calculated Attributes
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Warehouse Sync API Overview
Warehouse Sync API Tutorial
Warehouse Sync API Reference
Data Mapping
Warehouse Sync SQL Reference
Warehouse Sync Troubleshooting Guide
ComposeID
Warehouse Sync API v2 Migration
Bulk Profile Deletion API Reference
Calculated Attributes Seeding API
Custom Access Roles API
Data Planning API
Group Identity API Reference
Pixel Service
Profile API
Events API
mParticle JSON Schema Reference
IDSync
AMP SDK
Initialization
Configuration
Network Security Configuration
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IDSync
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Opt Out
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Logger
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API Reference
Upgrade to Version 5
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Identity
Direct URL Routing FAQ
Web
Android
iOS
Initialization
Configuration
Event Tracking
User Attributes
IDSync
Screen Tracking
Commerce Events
Location Tracking
Media
Kits
Application State and Session Management
Data Privacy Controls
Error Tracking
Opt Out
Push Notifications
Webview Integration
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Preventing Blocked HTTP Traffic with CNAME
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Troubleshooting iOS SDK
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iOS 14 Guide
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iOS 18 FAQ
API Reference
Upgrade to Version 7
Getting Started
Identity
Upload Frequency
Getting Started
Opt Out
Initialize the SDK
Event Tracking
Commerce Tracking
Error Tracking
Screen Tracking
Identity
Location Tracking
Session Management
Initialization
Configuration
Content Security Policy
Event Tracking
User Attributes
IDSync
Page View Tracking
Commerce Events
Location Tracking
Media
Kits
Application State and Session Management
Data Privacy Controls
Error Tracking
Opt Out
Custom Logger
Persistence
Native Web Views
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Web SDK via Google Tag Manager
Preventing Blocked HTTP Traffic with CNAME
Facebook Instant Articles
Troubleshooting the Web SDK
Browser Compatibility
Linting Data Plans
API Reference
Upgrade to Version 2 of the SDK
Getting Started
Identity
Web
Alexa
Node SDK
Go SDK
Python SDK
Ruby SDK
Java SDK
Overview
Step 1. Create an input
Step 2. Verify your input
Step 3. Set up your output
Step 4. Create a connection
Step 5. Verify your connection
Step 6. Track events
Step 7. Track user data
Step 8. Create a data plan
Step 9. Test your local app
Overview
Step 1. Create an input
Step 2. Verify your input
Step 3. Set up your output
Step 4. Create a connection
Step 5. Verify your connection
Step 6. Track events
Step 7. Track user data
Step 8. Create a data plan
Step 1. Create an input
Step 2. Create an output
Step 3. Verify output
Introduction
Outbound Integrations
Firehose Java SDK
Inbound Integrations
Compose ID
Data Hosting Locations
Glossary
Rules Developer Guide
API Credential Management
The Developer's Guided Journey to mParticle
Create an Input
Start capturing data
Connect an Event Output
Create an Audience
Connect an Audience Output
Transform and Enhance Your Data
The new mParticle Experience
The Overview Map
Introduction
Data Retention
Connections
Activity
Live Stream
Data Filter
Rules
Tiered Events
mParticle Users and Roles
Analytics Free Trial
Troubleshooting mParticle
Usage metering for value-based pricing (VBP)
Introduction
Sync and Activate Analytics User Segments in mParticle
User Segment Activation
Welcome Page Announcements
Project Settings
Roles and Teammates
Organization Settings
Global Project Filters
Portfolio Analytics
Analytics Data Manager Overview
Events
Event Properties
User Properties
Revenue Mapping
Export Data
UTM Guide
Data Dictionary
Query Builder Overview
Modify Filters With And/Or Clauses
Query-time Sampling
Query Notes
Filter Where Clauses
Event vs. User Properties
Group By Clauses
Annotations
Cross-tool Compatibility
Apply All for Filter Where Clauses
Date Range and Time Settings Overview
Understanding the Screen View Event
Analyses Introduction
Getting Started
Visualization Options
For Clauses
Date Range and Time Settings
Calculator
Numerical Settings
Assisted Analysis
Properties Explorer
Frequency in Segmentation
Trends in Segmentation
Did [not] Perform Clauses
Cumulative vs. Non-Cumulative Analysis in Segmentation
Total Count of vs. Users Who Performed
Save Your Segmentation Analysis
Export Results in Segmentation
Explore Users from Segmentation
Getting Started with Funnels
Group By Settings
Conversion Window
Tracking Properties
Date Range and Time Settings
Visualization Options
Interpreting a Funnel Analysis
Group By
Filters
Conversion over Time
Conversion Order
Trends
Funnel Direction
Multi-path Funnels
Analyze as Cohort from Funnel
Save a Funnel Analysis
Explore Users from a Funnel
Export Results from a Funnel
Saved Analyses
Manage Analyses in Dashboards
Dashboards––Getting Started
Manage Dashboards
Dashboard Filters
Organize Dashboards
Scheduled Reports
Favorites
Time and Interval Settings in Dashboards
Query Notes in Dashboards
User Aliasing
The Demo Environment
Keyboard Shortcuts
Analytics for Marketers
Analytics for Product Managers
Compare Conversion Across Acquisition Sources
Analyze Product Feature Usage
Identify Points of User Friction
Time-based Subscription Analysis
Dashboard Tips and Tricks
Understand Product Stickiness
Optimize User Flow with A/B Testing
User Segments
IDSync Overview
Use Cases for IDSync
Components of IDSync
Store and Organize User Data
Identify Users
Default IDSync Configuration
Profile Conversion Strategy
Profile Link Strategy
Profile Isolation Strategy
Best Match Strategy
Aliasing
Overview
Create and Manage Group Definitions
Introduction
Catalog
Live Stream
Data Plans
Blocked Data Backfill Guide
Predictive Attributes Overview
Create Predictive Attributes
Assess and Troubleshoot Predictions
Use Predictive Attributes in Campaigns
Predictive Audiences Overview
Using Predictive Audiences
Introduction
Profiles
Warehouse Sync
Data Privacy Controls
Data Subject Requests
Default Service Limits
Feeds
Cross-Account Audience Sharing
Approved Sub-Processors
Import Data with CSV Files
CSV File Reference
Glossary
Video Index
Single Sign-On (SSO)
Setup Examples
Introduction
Introduction
Introduction
Rudderstack
Google Tag Manager
Segment
Advanced Data Warehouse Settings
AWS Kinesis (Snowplow)
AWS Redshift (Define Your Own Schema)
AWS S3 (Snowplow Schema)
AWS S3 Integration (Define Your Own Schema)
BigQuery (Snowplow Schema)
BigQuery Firebase Schema
BigQuery (Define Your Own Schema)
GCP BigQuery Export
Snowflake (Snowplow Schema)
Snowplow Schema Overview
Snowflake (Define Your Own Schema)
Aliasing
To integrate with Snowflake, you will need to access your Snowflake console.
For this self-service integration, we also have some data requirements:
For any advanced enrichments or modeling such as creating custom user aliasing logic, please contact us
Load Timestamp Field
Select the field used to identify new data. We recommend using a timestamp that denotes when the event was published, not the actual event timestamp to allow for late data to be collected. This will not impact your analyses since we reference the event timestamp for our queries. If you select to load data every 3, 6, or 12 hours, make sure to select a load timestamp field with at least hour precision (not a date only field).
For example, if an event with an event timestamp of 12/1 was published to the table on 12/3, this will not be collected unless we use the publishing timestamp since every daily extract would look for events that occurred on 12/3. Using the publishing timestamp will allow us to extract all new data that was published to the table on a nightly basis.
Start Date
Select the date from where Analytics should load your data from.
::: success If your data history exceeds 1 billion events, a Solutions Engineer will contact you to assist with the integration. :::
Click Next. After this step, we will perform a few checks on your data with the model that you provided. The checks are:
After some basic checks, we can define your users within your data. For more information on User Identification (Aliasing), please refer to this article.
If you choose to enable Aliasing:
If you choose to disable Aliasing, press Disabled:
If you have a non-null value that represents null UserID values, please click on the Show Advanced button. In this field, please enter these non-null values.
::: success After this step, we will perform additional checks on your data with the user model that you provided. The checks are:
You should see a summary of your data based on the last 7 days in two main blocks. You should only be concerned if the margin of error is significant. If so, please reach out to a product specialist:
Events Summary
You should see a daily breakdown of your Total Event Count, and the number of Unique Event Names. If there are certain events to exclude, please click on the Exclude checkbox for those events.
If you would like to exclude any events by regex or property value, please contact a product specialist.
Properties Summary
Here you will see the number of Unique Property Names. If there are certain properties to exclude, please click on the Exclude checkbox for those events.
If you require more advanced configurations such as parsing out JSON fields, creating derived properties, or excluding properties based on regex, please contact a product specialist.
If you see this screen, you’re all done! You should see your data in Analytics within 48-72 hours and will be notified by email.
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