A properly designed data integration process is THE key step to combine different data sources by adapting their format, fields and the way they are consumed. For this to happen, ETL (Extract, ...

And before that data is ready for analysis, it needs to be combined, cleaned, and normalized—a process otherwise known as extract, transform, load (ETL)—which can be laborious and error-prone.

AI data analytics simplifies and automates this process for business users ... along with a range of AI data analytics ...

I'd like to share insights on the interplay between AI and data integration in reshaping the analytics landscape.

And customers reported challenges with scaling ETL workloads with millions ... parallel working, data streaming, logging and process status communications. Niche Player: Fivetran Fivetran also ...

A significant chasm exists between most organizations’ current data infrastructure capabilities and those necessary to ...

Data engineering refers to the process of creating systems for collecting, storing and analysing large amounts of data.

PuppyGraph, the first and only graph query engine, announced today its $5 million seed funding round led by defy.vc. The zero ...

With the pace of change in the tech world only increasing, the need to innovate and be agile is no longer a nice to have; it’s a must-have. Amit Taneja is a good example of this type of mindset.

Artificial intelligence (AI) has been all the rage lately with OpenAI’s evolution and consumer adoption of various use cases.