Incremental Load & JSON Processing Workflow Orchestration on Azure
Learning objective
- Incremental Data Processing:
- Extract meaningful insights
- Work with triggers
Overview
Understanding how to implement an incremental load pipeline to process real-time data updates, extract specific metrics, and load the processed data to a suitable data store.
Story
Global Mart is one of the leading e-Commerce giants with a presence in North America and Europe region. It has a presence across 120 markets and primarily deals with 3 lines of business :
- Technology,
- Office Supplies
- Furniture
The Data Engineering team faces a pivotal challenge: orchestrating a data pipeline that seamlessly merges historical sales data with real-time updates arriving every 10 minutes. The objective is to automate the task of analyzing the data and extracting valuable insights.
Congratulations on being selected to spearhead the development of this crucial pipeline for GlobalMart! As the lead developer, your responsibilities encompass:
- Pipeline Architecture and Design: Craft a robust architecture for the incremental load pipeline, ensuring seamless integration of historical and real-time data. Design the ETL flow to efficiently transform and process data updates every 10 minutes.
- Data Transformation Logic: Develop the logic to extract and compute the required metrics. Guarantee the accuracy and reliability of these insights.
- Integration with Data Storage: Establish the connection between the pipeline and the Data Lake, creating a reliable mechanism to store processed data. Ensure data integrity and adherence to data quality standards.
- Automation Implementation: Set up triggers and scheduling mechanisms to automate the execution of the pipeline at 10-minute intervals. Maintain and optimize these automated processes for consistency and efficiency.