AEP : Identity and identity graphs 

Adobe Experience Platform's Identity Service, which helps you connect your customer's scattered data to build a unified view of them.

Think of it as solving a puzzle where each piece is a separate clue about a customer from different places (website, app, in-store). The Identity Service finds how these pieces fit together by linking different IDs (like email, CRM ID, device ID) that all belong to the same person. This linking creates a map of relationships called an Identity Graph.

Here’s how it works in three key steps:

Step	What It Does	Simple Analogy
1. Identity Collection	You label fields like "email" or "customer ID" as identity fields in your data. When data is imported, the system spots these labels.	You tag different puzzle pieces with the same color if they belong to the same customer.
2. Identity Graph	The system uses deterministic rules to link IDs found together (e.g., when a website visitor logs in, linking their anonymous ID to their account ID). It builds a private "graph" or map of all these connections for each person.	You physically connect the matching puzzle pieces, building a complete picture.
3. Identity Service API	Developers can use this API to work with the identity graphs in their own apps, just like the Adobe Platform interface does.	You can now show the completed puzzle picture on different screens or use it in different ways.

💡 Why This Matters

This service solves the common problem of data being stuck in separate "silos" (like CRM, website, app data). By linking identities, you can create a Real-time Customer Profile, which is a single, complete view of each customer. This unified view allows you to personalize their experience seamlessly across all your brand's touchpoints.

Imagine you're a detective trying to solve the mystery of "Who is Customer X?"

You have clues scattered in different notebooks: one notebook has a customer's email address from your online store, another has their phone number from a support call, and a third has their loyalty card ID from in-store purchases.

Your job is to figure out that alice@email.com, (555) 123-4567, and LoyaltyMember#88241 are all the same person—Alice. Adobe Experience Platform's Identity Service is your high-tech system for doing exactly that.

Here’s how it works, broken down into three simple steps with examples:

🏷️ Step 1: Label the Clues (Label Data as Identities)

This is where you tell the system, "Hey, this piece of information is a unique clue to someone's identity."

• Example: In your "Online Store" notebook (dataset), you mark the Email field as an "Identity." In your "Loyalty Program" notebook, you mark the Loyalty Card Number as an "Identity."
• The Key Choice - Namespace: A namespace is just the type of clue. Is it an Email? A Phone Number? A CRM ID? You pick the right type so the system knows how to handle it.
• The Special Clue - Primary Identity: You pick one main clue per notebook that is the most reliable. For your "CRM System" notebook, the best, most consistent clue might be the crm_id. This becomes the primary key to find that person's main profile.

⚠️ Important: Just like a real detective, you must work with your legal/privacy team. Decide which clues you are allowed to collect and connect, respecting customer privacy.

📥 Step 2: Combine the Notebooks (Ingest Identity Data)

Now, you feed all your notebooks (datasets) into the detective's system (Adobe Experience Platform).

• Example: You upload the data from your Online Store, your CRM, and your Loyalty Program. Because you already labeled the clues (Email in one, Loyalty ID in another), the system gets to work.
• The Magic (Private Graph): The system sees that alice@email.com (from an online order) is linked to LoyaltyMember#88241 (from a store purchase) because they appeared together on a single receipt. It creates a hidden, connected web—a private identity graph—showing these are the same person. Alice's profile is no longer three separate fragments; it's starting to unify.

✅ Step 3: Check Your Work (Verify the Data)

Finally, you check the system's case files to confirm the connections were made.

• Example: You go to the Identities page in Adobe, look up alice@email.com, and the system shows you all the other connected IDs (phone, loyalty ID) that are now stitched to her single customer profile. You've successfully solved the mystery!

Real-World Analogy: The Hospital System

Think of a modern hospital with different departments:

• The Emergency Room knows you by your Driver's License.
• The Lab knows you by your Lab Order ID.
• The Billing Department knows you by your Account Number.

A good hospital system labels these IDs, ingests records from all departments, and uses an Identity Graph to link them all to you, the single patient. This way, any doctor can see your complete history, no matter which department you visited first.

Summary in One Sentence:

You tell the system which data points are customer IDs (label), send in your customer data (ingest), and check that the system correctly linked everything (verify) to build a complete, single view of each customer.

Identity Graph Viewer

Identity Graph Viewer in Adobe Experience Platform. It's a tool designed for data engineers to inspect and debug how customer identities are connected, or "stitched" together.

Think of it as a "debugging window" that makes the invisible process of identity stitching visible and easy to understand. Before this tool, the process was essentially a "black box" for engineers, making it hard to validate if data was ingested correctly or to find errors in profile unification.

Here are the tool's key features:

• 🔍 Search & Explore: You can search for a specific identity (like an email or CRM ID) and see a graphical map of all its linked identities.
• 👁️ Visual Graph View: The main display is a visual graph where each circle (node) is an identity (e.g., email, phone, device ID) and the connecting lines show how they are linked.
• 🔧 Debug with Details: Clicking on any identity node or connection line reveals detailed metadata. This includes which datasets created the link, batch IDs, and timestamps, helping you trace the source of any data or stitching issue.
• 📊 Data Source Timeline: A separate tab shows a timeline of all data sources ingested, allowing you to see exactly when and how new data contributed to building or changing the graph.

💡 How It Solves Real Problems

The tool is especially useful for two critical scenarios:

1. Validation: After ingesting new data, you can check if identities are stitching together as expected.
2. Debugging: If you suspect an error—such as two unrelated customer profiles being incorrectly linked—you can use the visual graph to spot these "collapsed" clusters and investigate the specific data batches that caused the connection.