Use Cases

Evolve from batch to real-time customer data analytics with mParticle and Amazon Kinesis

Data-driven teams can’t afford to have batch querying and reporting anymore. It's becoming increasingly important to turn customer data into actionable insights quickly.

Innovative product and engineering teams are continuously looking to evolve their applications to support real time customer data analytics by utilizing event data processing, click-stream analysis, and real time user behavior analytics.

Step 1: Real-time data collection

The foundation of any data pipeline is the data collection and quality management. mParticle's native SDKs and APIs enable you to collect customer data from both client side and server side environments to help you gain a full picture of engagement while supporting responsible data governance. All data collected is validated against your data plan and resolved to unique customer profiles to ensure data quality.

Step 2: Decide which data to forward

Once you have access to a high-quality data set in mParticle, you can use mParticle's Amazon Kinesis Event integration to easily pipe your data into a Kinesis Data Stream without having to install a Kinesis library or making any modifications to your code. All that's needed to set up the integration is the Stream Name, Kinesis Service Region, and either the credentials of an Identity and Access Management (IAM) user that has access to Kinesis, or the AWS Account ID of the role mParticle will assume, depending on the setup option taken. Data is forwarded from mParticle to Kinesis as it is received. Control which events are forwarded using Data Filtering within the mParticle UI.

mParticle Data Filtering overview

Following is an example format of the events batch:

{
   "events" :
   [
       {
           "data" : {},
           "event_type" : "custom_event"
       }
   ],
   "device_info" : {},
   "source_request_id":"7fa67be4-f83a-429f-9d73-38b660c50825",
   "user_attributes" : {
     "firstName": “John”,
     "lastName": “Doe”,
     "email": "john.doe@mparticle.com",
     "referrer": "https://www.mparticle.com/"
    },
   "deleted_user_attributes" : [],
   "user_identities" : {},
   "application_info" : {},
   "schema_version": 2,
   "environment" : "production",
   "context": {},
   "mpid":7346244611012968789,
   "ip" : "10.10.10.10"
}

KDS makes your streaming data available to multiple real-time analytics applications, to Amazon S3, or to AWS Lambda within 70 milliseconds of the data being collected.

You can then use existing business intelligence tools and dashboards to analyze customer data in real time or enable your developers to build custom applications that analyze streaming data, real-time anomaly detection, dynamic pricing, and more.

Amazon Kinesis

See the documentation

Step 1: Real-time data collection Step 2: Decide which data to forward

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