If you're considering using a data integration platform to build your ETL process, you may be confused by the terms data integration and ETL. Here's what you need to know about these two processes.

Getting a handle on your entire, hybrid data landscape starts with a thorough data discovery and dependency mapping process along with an impact analysis. Here’s how to pull it off.

Data integration is the process of combining data from multiple sources into a single target data store. Learn more now.

This initial portion of the data integration process can be decomposed into an actionable workflow, which may be automated and repeatable across projects. Specifically, the pre-ETL (extract, transform ...

This is where enterprise software vendors differ in terms of the quality of data integration and how they help their customers improve decision-making.

In the new round of competition for industrial internet technologies, Nantong Wu Xi Information Technology Co., Ltd. has delivered a new response. The company applied for a patent titled ...

AI can improve data integration by automating and quickly accomplishing what used to be manual or time-consuming tasks.

In data integration, data fabric is about eliminating human effort, while data mesh is about smarter and more efficient use of human effort.

In the context of data integration, the ability to monitor and understand the flow of data is key to ensuring the quality and reliability of data as it moves through various stages of the integration ...

Informatica is aiming to ease the pain of data integration with a new platform designed to allow businesses to rapidly prototype and validate before sending projects to development.