Building a BDB Data Pipeline

This section will provide a step-by-step guide for getting started with the BDB Data Pipeline module, from initial setup to deployment.

Here, you will learn how to visually author a data pipeline using the low-code interface, connect different data processing components, integrate custom Python scripts for complex logic, and set up event-based orchestration for your workflows. The guide will cover essential tasks for new users, such as reading from a source, transforming data, and writing to a destination.

Sample Use Case: Real-Time Order Processing

A common application for the BDB Data Pipeline is automating business processes that require real-time or near-real-time data flow. An example of this is a sales order processing system.

Scenario: A new sales order is created in your e-commerce system.

1. The sales order data is immediately published to a Kafka topic, which acts as a connecting component.

2. The BDB Data Pipeline, designed to "listen" for these events, automatically kicks off the order processing job as soon as the data is pushed to the Kafka topic.

3. Within the pipeline, a series of components can perform various tasks on the data, such as:

   1. Enrichment: Adding customer details by joining the order data with a customer database.

   2. Validation: Ensuring all required fields (e.g., product ID, quantity) are present and correctly formatted.

   3. Aggregation: Calculating the total order value, including taxes and shipping.

4. Once the data is transformed and validated, the pipeline can use a Writer component to update relevant systems, such as an inventory management system to deduct the sold items and a financial system to record the transaction.

5. The entire workflow is automated, with the process gracefully terminating upon completion.

This event-driven approach ensures that the entire order-to-fulfillment process is handled with minimal latency, providing immediate insights and enabling rapid updates to all connected business systems.

(Need a support video to display the entire process).