Policing data hosted in Microsoft’s hyperscale cloud infrastructure could be processed in more than 100 countries, but the tech giant is obfuscating this information from its customers, Computer ...

Data literacy, the ability to read, understand, analyze and communicate information, helps companies make better decisions, improve performance and data visualization, and better manage risks and ...

The city of Harwood houses fewer than 800 people. Soon, it will be home to a 280-megawatt artificial intelligence data center. A mockup of Applied Digital’s 280-megawatt data center, or AI factory, ...

Who needs rewrites? This metadata-powered architecture fuses AI and ETL so smoothly, it turns pipelines into self-evolving engines of insight. In the fast-evolving landscape of enterprise data ...

A metadata-driven ETL framework using Azure Data Factory boosts scalability, flexibility, and security in integrating diverse data sources with minimal rework. In today’s data-driven landscape, ...

Forbes contributors publish independent expert analyses and insights. I write about how fintech is disrupting the financial industry in Asia.

Microsoft has taken significant steps to standardize how artificial intelligence models interact with cloud data by unveiling public previews for two distinct Model Context Protocol (MCP) servers. The ...

The edge is a dynamic environment where data is created by a multitude of devices—sensors, cameras, IoT devices, and more. Managing and orchestrating applications across far-flung edge locations can ...

Azure Data Studio will officially be retired on February 28, 2026. Microsoft just announced the retirement in a blog post, recommending that all users try out the alternatives: Visual Studio Code and ...

As part of an ongoing human resources transformation across Microsoft, the company is using Microsoft Azure Data Lake to do more with its HR data. Editor’s note: This content was first published in ...

Abstract: Data wrangling is a critical yet often labor-intensive process, essential for transforming raw data into formats suitable for downstream tasks such as machine learning or data analysis.

Free use and redistribution of data (i.e., Open Data) increases the reproducibility, transparency, and pace of aquatic sciences research. However, barriers to both data users and data providers may ...