Real-Time Data Processing with Delta Live Tables: Use Cases and Best Practices for Databricks

Image Source: https://blog.atawiz.fr/article/pipeline-databricks-deltalake-tables/

After explaining Delta Live Tables (DLTs) in Databricks and how to incorporate them into data pipelines in my previous post, I wanted to take a deeper dive into some specific use cases of Delta Live Tables.

What are Delta Live Tables again? Delta Live Tables, often abbreviated as DLTs, are used to manage real-time data pipelines. They can handle large volumes of data ingestion making them ideal for quick insights and analysis.

Before I go into some practical use cases of DLTs, they’re many advantages for using DLTs in your pipelines and data strategy:

Key Advantages of DLTs:

• Real-Time: DLTs empower you to process and analyze data as it arrives, eliminating lag from batch streaming.
• Data Quality Assurance: With constraints and expectations, DLTs ensure the integrity and quality of your data.
• Multi-Hop Architecture: DLTs are within the medallion or multi-hop architecture, satisfying the multi-layer approach to data pipelines.

Here I provide two use cases for DLTs that may provide a lot of meaningful insights to your data streaming pipelines