KDNuggets, a community site for data professionals, ranked “We Don’t Need Data Scientists, We Need Data Engineers,” by Mihail Eric, a venture capitalist, researcher, and educator, as its top story of ...

Data engineering and data science are complementary disciplines that have come to define modern approaches to managing, processing, and extracting value from vast and complex data sets. Data ...

As businesses continue to harness Big Data to drive innovation, customer engagement and operational efficiency, they increasingly find themselves walking a tightrope between data utility and user ...

Today, Microsoft is announcing the acquisition of Osmos, an agentic AI data engineering platform designed to help simplify complex and time-consuming data workflows. Microsoft + Osmos: Extending ...

Big data engineering company dbt Labs Inc. today announced it’s buying SDF Labs Inc. in a merger of acronymic startups that promises to deliver improved data velocity and quality for their customers.

The modern business landscape is being fundamentally reshaped by the convergence of cloud computing, big data, and artificial intelligence. This technological trinity is no longer a futuristic concept ...

In a world where data is the key to business success, data engineers are the architects of transformation. Harsha Kamma is one such architect, driving groundbreaking change in how companies handle ...

Though the AI era conjures a futuristic, tech-advanced image of the present, AI fundamentally depends on the same data standards that have been around forever. These data standards—such as being clean ...

The demand for data engineering solutions is growing significantly. According to a Market Data Forecast report, the global big data and data engineering market was valued at $75 billion in 2024 and is ...

The latest trends in software development from the Computer Weekly Application Developer Network. This is a guest post for the Computer Weeklyu Developer Network written by Jesse Anderson in his role ...

(a) Crop breeding driven by the next generation of AI and big data technologies will be revolutionized in four areas: (i) high-throughput phenotype acquisition and analysis; (ii) biological big ...