Data Warehouse
The attached sequence diagram appears to depict a high-level overview of a data processing system. Here’s a breakdown of the interaction flow:
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.
Data Warehousing: The data is streamed from the Kafka Cluster to a Data Warehouse. A DWH is a central repository for storing historical data.
Data Transformation: Data Intelligence takes the streamed data and transforms it into a format suitable for further analysis.
Campaign Data Transmission: Once transformed, the data is then sent to a Kafka Cluster designated for Campaigns.
Campaign Processing: Data is processed by the Campaign Engine, which is responsible for configuring and launching the campaign.
Delivery to Transactions Center: After processing, the Campaign Kafka Cluster sends the data to a Transactions Center.
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.
User Data Transmission to Transactions Center: From the Kafka Cluster, Users’ data is then delivered to the Transactions Center.
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