Data Subject Request API Version 1 and 2
Data Subject Request API Version 3
Platform API Overview
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Warehouse Sync API Overview
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ComposeID
Warehouse Sync API v2 Migration
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mParticle JSON Schema Reference
IDSync
AMP SDK
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Upgrade to Version 7
Getting Started
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Getting Started
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Location Tracking
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Location Tracking
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Kits
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Opt Out
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API Reference
Upgrade to Version 2 of the SDK
Getting Started
Identity
Web
Alexa
Introduction
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Compose ID
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Migrate from Segment to mParticle
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Migrate from Segment to Server-side mParticle
Segment-to-mParticle Migration Reference
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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
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
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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
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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
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Favorites
Time and Interval Settings in Dashboards
Query Notes in Dashboards
User Aliasing
The Demo Environment
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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
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Optimize User Flow with A/B Testing
User Segments
IDSync Overview
Use Cases for IDSync
Components of IDSync
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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
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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
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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 Integration (Define Your Own Schema)
AWS S3 (Snowplow 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
Every query requires you to define a date range. The date range refers to the time period that you would like to analyze. All new queries default to the Last 7 Days. To open the date range selector dropdown, select Last 7 Days. The start date is the first day to be included in the search. The end date is the last day.
To select fixed start and end dates, use the date range selector on the left side of the dropdown and select a start date and end date from the calendar. You can also enter a specific date by selecting the date at the top of the selector and entering a value. Use the left and right arrows to navigate the calendar. Select the Today checkbox to create a dynamic end date.
The right side of the dropdown lists all of the dynamic date ranges that are available. You may choose a dynamic date range, for example Last 7 Days or Last Full Month. This will automatically update the date range of your query, counting backwards from today. If you select Last Full Week, then Analytics will analyze the most recent complete week, defined as Monday to Sunday. If you choose Last Full Month, then Analytics will analyze the most recent complete month. You can quickly navigate the calendar to select full months using the links in the lower left corner of the dropdown.
To save a new custom date range, for example “Last 45 Days,” simply choose Add Custom Date Range in the lower right corner of the dropdown. Your previously used custom date ranges will be saved for future use and are viewable alongside the default dynamic date ranges.
Note: Custom relative date ranges are saved within each individual user’s account, rather than for all users across a particular project.
In Segmentation, you may also exclude any recent partial intervals. For example, if you’re measuring a query with a monthly frequency, but you happen to be querying in the middle of the month, you can exclude the most recent, partial month from your visualization area.
In order to visualize your data, the date range will be organized into units of time called intervals.
You may choose Hourly, Daily, Weekly, or Monthly intervals. Hourly is our smallest interval that you can run analysis on. For weekly intervals, Analytics considers the week to start on a Monday.
Interval options are dependent on the date range selected. For example, if the selected date range is Last 7 Days, then the available time intervals will be Hourly, Daily, and Full Range. Weekly will not be available because there is only one week in a seven day date range. If the date range is changed to Last 90 Days, then the intervals dropdown will update with the additional options of Weekly and Monthly, but will no longer allow Hourly analysis due to visualization constraints. To calculate the total event or user count across an entire date range, select Full Range.
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