🔥 ETL vs ELT: What's the Difference?

When it comes to data processing, two key approaches stand out: ETL and ELT. Both involve transforming data, but the processes differ significantly!

🔹 ETL (Extract, Transform, Load)
- Extract data from various sources (databases, APIs, etc.)
- Transform data before loading it into the storage (cleaning, aggregating, formatting)
- Load the transformed data into the data warehouse (DWH)

✏️ Key point: Data is transformed before being loaded into the storage.

🔹 ELT (Extract, Load, Transform)
- Extract data from sources
- Load raw data into the data warehouse
- Transform the data after it's loaded, using the power of the data warehouse’s computational resources

✏️ Key point: Data is loaded into the storage first, and transformation happens afterward.

🎯 When to use which?
- ETL is ideal for structured data and traditional systems where pre-processing is crucial.
- ELT is better suited for handling large volumes of data in modern cloud-based architectures.

Which one works best for your project? 🤔