Bhagya Laxmi Vangala is an experienced data engineering architect with more than 16 years of experience specializing in ...

Supports all workloads, including ETL, extract-load-transform, batch, streaming and more. Scales on demand to handle any data size. Users can discover and connect to over 70 diverse data sources.

How can companies ensure they’re producing clean, extensible, enriched insights that are accessible to colleagues across an organization and partners alike?

When its custom data pipelines began to fail at scale, one team pragmatically chose a single tool to create momentum, valuing ...

The extract-load-transform process has become increasingly important over the past 10 years, with the advent of big data, data lakes and cloud-based data storage. Those same white papers and blogs ...

Today, ETL, along with its cousin Extract, Load, Transform (ELT), is used within increasingly complex data frameworks, including the internet of things (IoT), connected supply chains, cloud ...

SUNNYVALE, Calif., Feb. 23, 2011 (GLOBE NEWSWIRE) -- Queplix™ Corp., a leader in data virtualization, today announced two new product families that bring the power of data virtualization to the ...

For many organizations, there may be a bottleneck in the ETL (extract, transform, load) process that hampers speed. There must be a solution in place to solve that pain point.

Image: canjoena/Adobe Stock. The E, T and L in both ETL and ELT stand for extract, transform and load. However, their ordering is what differentiates how they function and process data.

Amazon made a couple of announcements today at AWS re:Invent in Las Vegas that helps move data management toward a future without the need for extract transform load, or ETL.