Data Warehouse

Data Warehouse Flow

The attached sequence diagram appears to depict a high-level overview of a data processing system. Here’s a breakdown of the interaction flow:

1. Data Acquisition: The process begins with raw data being sent from Databases to a Kafka Cluster. Kafka Cluster is a platform for handling real-time data feeds.

2. Data Warehousing: The data is streamed from the Kafka Cluster to a Data Warehouse. A DWH is a central repository for storing historical data.

3. Data Transformation: Data Intelligence takes the streamed data and transforms it into a format suitable for further analysis.

4. Campaign Data Transmission: Once transformed, the data is then sent to a Kafka Cluster designated for Campaigns.

5. Campaign Processing: Data is processed by the Campaign Engine, which is responsible for configuring and launching the campaign.

6. Delivery to Transactions Center: After processing, the Campaign Kafka Cluster sends the data to a Transactions Center.

7. User Data Processing: In parallel with the Campaign data processing, the Data Intelligence unit also produces users’ data. This data is then sent to a separate Kafka Cluster.

8. User Data Transmission to Transactions Center: From the Kafka Cluster, Users’ data is then delivered to the Transactions Center.