Get started with model-based Schemas and Datasets gs-schemas
This guide walks you through the process of creating a model-based schema, configuring a dataset for Orchestrated campaigns and ingesting data.
Key concepts
In the context of Orchestrated campaigns, a dataset is a storage and management construct for a collection of data, typically a table, that contains a schema (columns) and fields (rows). Data that is successfully ingested into Experience Platform is stored within the data lake as datasets.
A schema represents and validates the structure and format of data. It provides an abstract definition of a real-world object (such as a person) and outlines what data should be included in each instance of that object (such as name, birthday, and so on).
A data model is the conceptual blueprint of normalizing your data
It describes:
- The entities (e.g., Customer, Campaign, Segment)
- The attributes of those entities (e.g., Customer Name, Campaign Start Date)
- The relationships between entities (e.g., Customers belong to Segments, Campaigns target Segments)
A data model is logical and conceptual, not tied to a physical implementation in Orchestrated Campaign
In a model-based data model, data is organized into tables relating to other tables.
- Each table has rows(records) and columns(attributes)
- Every table has a primary key to uniquely identify rows
- Relationships between tables are expressed using foreign keys
A model-based schema is the formal definition of the model-based data model.
It specifies:
- The set of tables
- The columns in each table
- The constraints
- The relationships across tables
Organizing schemas or tables in a model-based data model is about structuring your data into multiple tables. Ensure each table stores one type of entity/schemas
Implementation steps implementation
To ingest data and create model-based schema, follow these steps:
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Create model-based schema manually or using a DDL file
Define the structure of your data model, including tables, attributes, and relationships. Choose to build the schema manually in the user interface or upload a DDL file for faster setup.
When creating the schema manually, dataset must also be created and enabled manually. When using a DDL file, dataset creation and enablement are automatic.
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Establish relationships between your schemas to ensure data consistency and enable cross-entity queries. For example, link loyalty transactions to recipients or rewards to brands.
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After defining your schema, you need to create a dataset based on it. This dataset acts as the storage for your ingested data.
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The dataset stores your ingested data and must be enabled for Orchestrated Campaigns to ensure it is accessible in Adobe Journey Optimizer.
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Bring data into Adobe Experience Platform from supported sources such as SFTP, cloud storage, or databases.