Introduction to Datastreams

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Today, we will discuss one of the most vial parts of setting up your data collection for Adobe App Services: the datastreams. Now, imagine this: your organization has recently started using Adobe Analytics and you want to set up your data collection so that you can start generating reports. You excitedly sign into your Adobe Account, go to your Experience Dashboard, and click on the Data Collection service. However, now you are stuck on the Home Page and don't know what to do next. What should you do first and how do you navigate this service? One tool required to setup is the datastream.  

Before we delve into datastreams, we should do a quick high-level overview of how data arrives to the stream in the first place. Your organization is probably leveraging a data layer (often called digitalData) to surface page attributes and a tag manager like Adobe Tags to load the Web SDK library. When an event is triggered (likely a sendEvent() command), the recorded data is sent to the Edge Network. Once the data is in the server, we need a way to send that data to all of the various Adobe or non-Adobe products that your organization desires. This is where datastreams come in to help. 

On one level, think of datastreams as a central hub that controls all of the data that is coming into your servers. Or think of datastreams as a traffic coordinator who makes sure all of the data is going to their proper destinations without colliding with each other. A datastream is going to ensure that your data will be sent to various Adobe products, like Adobe Analytics, Adobe Experience Platform, Adobe Target, etc. Furthermore, you can set up Event-Forwarding to send the data to any data warehouse, or any other platform like Google or Meta for your organization's use. 

Along with being a hub for data distribution, datastreams are also where data transformations or configurations occur before they are sent out to their respective destinations. This service is called data preparation and a few features of data preparation include mapping items in a datalayer to an XDM Schema, creating calculated fields, or capturing certain substrings within a field for reporting purposes. Additionally, you can set up geolocations, device lookups, bot filtering, and more. As a result, a datastream can also be thought of as a construction site where configurations are applied through data preparation to the events/data that is arriving to the Edge network before being sent out. 

Datastreams are vital to your data collection. Datastreams ensure your data will be sent to their proper destinations and enables data preparation so that the data is sent in the right format to their respective products.  

References: 

1. Experience League Live, https://experienceleague.adobe.com/en/docs/events/experience-league-live-recordings/episodes/exl-liv...
   1. WebSDK Introduction: 10:25 - 12:15  
   2. DataStream Intro: 12:15 - 14:45 
   3. Visual Diagram of Data Collection and Data Prep (High-Level overview of Datastreams): 18:00 - 20:00 
   4. Live Demo of Creating a DataStream: 20:40 - 23:39  
   5. Sending Data From the DataStream (Adding Services to the DataStream): 23:40 - 28:20 
   6. Mapping those Data into those XDM Schemas (Integration into Schemas): 29:00 - 34:23 
   7. Creating Calculated Fields in Data Prep: 34:25 - 35:54 
   8. Aligning DataStreams to your Tags  Property (or Site): 36:20 - 38:27 
   9. Creating Rules to Trigger that SDK to send that data. 38:33 - 40:00  
   10. Data Preparation and Ingestion Blueprint: 48:00 - 49:00 
   11. Data Mapping in the DataStream  (Technical Summary of Concepts): 49:58 - 59:40