Data Subject Request API Version 1 and 2
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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
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Sync and Activate Analytics User Segments in mParticle
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Apply All for Filter Where Clauses
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Analyses Introduction
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Group By
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Manage Analyses in Dashboards
Dashboards––Getting Started
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Aliasing
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Introduction
Introduction
Introduction
Rudderstack
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Segment
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AWS Kinesis (Snowplow)
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Snowplow Schema Overview
Snowflake (Define Your Own Schema)
Aliasing
Segmentation is Analytics’ most popular customer analytics tool. It offers a simplified query builder to generate fast, meaningful results and create informative visualizations. Ask, answer, and act on the most important questions about your customers and their behaviors.
Within the query builder, you’re able to construct a complex data search using a variety of field types. Every Segmentation query begins with an event. Start by setting whether you’d like to calculate the total count of events or the number of users who performed a particular event.
Additionally, you may categorize your results by using the Group By function or narrow your search by using a Filter Where function.
The Group By and Filter Where function are akin to SQL “group by” and “where” clauses. You can use event properties, user properties or user segments with any event you select in your segmentation.
Event properties are tied to a single instance of an event
User properties can be chosen on any event regardless if it came in with an event since it’s part of the user’s profile.
User Segments cross check user identities from their segment memberships.
Finally, you can create a combination of events by using additional For Clauses (+Did [Not] Perform).
You can also run a Frequency query to group users into different segments based on the number of times they performed a particular event.
All queries within Analytics are fully customizable using Settings such as the date range and interval. Event queries may display results on a per-interval basis or as a cumulative count. There are six different chart types to choose from:
Optional settings include Annotations, which mark milestone events, and Data Labels, which communicate the numerical values at each point in the chart.
For more advanced analysis, you may create queries with multiple rows, displaying and comparing information of distinct events within the same results. You may also create calculated queries to explore, for example, proportions or percentages using the Calculator. Finally, you may compare results to a previous interval by using the Trends function.
Certain analyses run in the past can change based on what user properties are set to since user properties can change over time. A common scenario where changes are seen when running analysis at different points in time, is a direct result of looking at users who were aliased since then.
Note on Aliasing: Aliasing runs once on a daily basis and links unknown users to known users. The count of unique users triggering an event seen before the aliasing process may decrease after aliasing finishes processing. You can read more by visiting our docs on user aliasing.
A few helpful tools are located to the right of the query builder:
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