Successful data strategies are built on a foundation of meticulous data management, creating enterprise architectures that “democratize” data access and usage, yielding measurable results from machine ...

The problem is wasteful supply chains clogged with excess inventory and defective parts. The goal is creating “perfect flow” for manufacturers and retailers to reduce waste running into the ...

At first glance, the data fabric and the data mesh concepts sound quite similar. Meshes are often made from a type of fabric, after all, and they are both malleable items that can be lain atop ...

During a presentation at Nvidia’s GPU Technology Conference (GTC) this week, the director of data science for Walmart Labs shared how the company’s new GPU-based demand forecasting model achieved a ...

With the National Institute of Standards and Technology (NIST) set to publish the first Post Quantum Cryptography (PQC) Standards in a few weeks, attention is shifting to how to put the new ...

Since the data fabric concept debuted a few years ago, it has become a popular method for enterprises to integrate disparate data management tools. Fabrics are yielding dividends for users, but ...

One of the hottest areas of big data at the moment is log monitoring and its adjacent disciplines, AIOps and cloud observability. The market, which some estimate is worth $17 billion per year, is in ...

The days of databases existing as islands unto themselves are over, according to Gartner, which reports the existence of a strong and growing signal for cloud databases to become part of “broader data ...

In this age of information, to say that the volume of data is exploding is a stark understatement. This big bang of big data is estimated to grow from 33 zettabytes in 2018 to 175 zettabytes by 2025, ...

Matei Zaharia, the creator of Spark and CTO of commercial Spark developer Databricks, shared his views on the Spark phenomena, as well as several real-world use cases, during his presentation at the ...

Should you strive to centralize your data, or leave it scattered about? It seems like it should be a simple question, but it’s actually a tough one to answer, particularly because it has so many ...

Data scientists spend about 45% of their time on data preparation tasks, including loading and cleaning data, according to a survey of data scientists conducted by Anaconda. The company also analyzed ...