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Managing data

Suggest edit Updated on September 21, 2021

Create and manage your customer data model. Make sure that you identify the customer data that correlates to your business use case and that is aligned with the problem that you want to solve.

Data Model

The Pega Customer Decision Hub application integrates your customer data to provide next best actions, execute marketing campaigns, and learn customer behavior using predictive and adaptive analytics.

The following diagram represents a typical Pega Customer Decision Hub implementation:

Pega Customer Decision Hub integration layer
Diagram showing data integration layer components in the client system and
                        Pega

The data in your systems of record is usually extracted to a data warehouse or data lake for internal purposes. Typically, only a portion of this data is required by the Pega Customer Decision Hub application. Pega supports accessing data through database ETL processes, batch file imports, or real-time services such as Kafka, Kinesis, or REST-based streams. Your project objectives and data latency requirements determine your data access implementation.

After the source data is identified, data is loaded to the out-of-the-box customer analytical data store. This process restructures the customer data as flattened data objects that maximize performance and scalability while ensuring data integrity. Designing the customer analytical data store is an important part of project initiation and should be done in conjunction with your business and implementation partners.

The customer analytical data store is also referred to as the Customer Analytics Record (CAR or xCAR). The xCAR is a flat, structured record of the customer data in a format that is optimized for performance and real-time analytics in one-to-one customer engagement. The result is a solution that provides more accurate and faster business decisions and that presents customers with messages and offers that are more attractive and better tailored to their needs.

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