Data engineers should be working faster than ever. AI-powered tools promise to automate pipeline optimization, accelerate data integration and handle the repetitive grunt work that has defined the ...

After unveiling a spate of features during its annual user conference in April, Qlik is now delivering some of the data engineering tools designed to prepare data for AI that had been in preview.

Data management, already of significant importance for operational and business intelligence purposes, has taken on a new level of priority for businesses and organizations as the wave of AI ...

Updates to Informatica's Intelligent Data Management Cloud (IDMC) are meant to maximize efficiency of an enterprise to handle complex challenges such as data integration, management and engineering.

Mukul Garg is the Head of Support Engineering at PubNub, which powers apps for virtual work, play, learning and health. In my journey through data engineering, one of the most remarkable shifts I’ve ...

As a data engineering leader with over 15 years of experience designing and deploying large-scale data architectures across industries, I’ve seen countless AI projects stumble, not because of flawed ...

AI success depends on whether enterprise data is ready, reachable, and close enough to the workloads that need it. In this eSpeaks episode, Dell Technologies’ Vrashank Jain explains why fragmented ...

Covers key topics like data wrangling, database schema, and developing ETL pipelines. He also details several data engineering tools like Hive, Hadoop, Spark, and Airflow. The courses offered in this ...

The latest trends in software development from the Computer Weekly Application Developer Network. This is a guest post for the Computer Weekly Developer Network written by James Sturrock, in his ...