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 Apache ...

ETL (extract, transform, load) migration is often treated as an afterthought when companies plan the migration of their on-prem data warehouses and data lakes to the cloud. Of course, ETL pipelines — ...

Using data fabric architectures to solve a slew of an organization’s operational problems is a popular—and powerful—avenue to pursue. Though acknowledged as a formidable enabler of enterprise data ...

In industries relying on up-to-the-minute insights, interruptions disrupt crucial processes, hindering timely responses to market changes and the accuracy of analytical outcomes. This can lead to ...

The Cloud ETL (Extract, Transform, Load) Tool Market was valued at USD 2.8 billion in 2024 and is projected to reach USD 10.5 billion by 2033, exhibiting a CAGR of 16.4% from 2026 to 2033. This ...

Data engineers historically have toiled away in the virtual basement, doing the dirty work of spinning raw data into something usable by data scientists and analysts. The advent of generative AI is ...