Data Engineering is the process of designing, building, and managing the systems and pipelines that collect, store, and prepare data for analysis or use in AI models. It focuses on ensuring data is accessible, reliable, and ready to be used.
Key tasks:
- Creating pipelines to move data from sources (like databases) to storage (like data warehouses).
- Cleaning, organizing, and transforming raw data into usable formats.
- Ensuring data systems can handle large volumes efficiently.
Example: A data engineer might set up a system to collect e-commerce sales data, clean it, and store it in a database so it can be analysed to improve marketing strategies or train AI models.
Data engineering is essential for making data usable in AI and analytics.