One popular subset of a data pipeline is an ETL pipeline, which stands for extract, transform, and load. While popular, the term is not interchangeable with the umbrella term of “data pipeline.” ...

Here's a closer look at how monitoring and alerting can act within an ETL system: • A continuous health assessment keeps a real-time check on the health of the ETL pipeline. This involves ...

Matillion built its ETL/ELT business during the last tectonic shift in the big data industry: the move from on-prem analytics to running big data warehouses in the cloud. It takes expertise and ...

Real-time pipelines, when constructed with care, help data engineers reduce latency, contain data proliferation and limit sprawl. Furthermore, these pipelines can process rich transformation ...

In this digital era, Gururaj Thite, a specialist in AI-driven systems and data infrastructure, unpacks the rapid advancements ...

AI-Powered ETL Pipelines: Data pipelines will become largely self-driving. AI-enabled ETL tools can adapt to changes in source data (for example, auto-adjusting to schema changes) and optimize ...

Snowflake today kicks off Data Cloud Summit 2020, the company’s first major public event since it raised $3.4 billion in a much-watched IPO two months ago. The summit offers a vehicle for Snowflake to ...

The ETL process is becoming EL (T), which means the data is first dumped as it is received in certain locations like a data lake. This way, the storage systems don’t complain about the format of ...

Data-integration pipeline platforms move data from a source system to a downstream destination system. Because data pipelines can deliver mission-critical data and for important business decisions ...

Today, at its annual Data + AI Summit, Databricks announced that it is open-sourcing its core declarative ETL framework as Apache Spark Declarative Pipelines, making it available to the entire ...