Enterprise AI is evolving rapidly, with trusted data and modern infrastructure playing crucial roles in its success. As organizations increasingly rely on AI to drive decision-making and innovation, ...

As organizations look to build out more complex digital frameworks, breaking down data silos is essential. But there’s a catch: As data analysts, data scientists and others work across various groups, ...

The evolution of data architecture is accelerating. In 2025, 85% of DBTA subscribers reported plans to modernize their data platforms — driven largely by the explosive rise of GenAI and large language ...

Becoming truly data-driven remains a key goal—and pressure—for organizations seeking to transform its infrastructures. Cultivating a modern, scalable data architecture, capable of delivering ...

The redesign of data pipelines, models, and governance frameworks is integral in facilitating the adoption of automation across asset servicing. Through re-engineering — which usually involves ...

Businesses are racing to harness sprawling data across multiple cloud platforms. Ashitosh Chitnis stands at the forefront of this movement—an architect of scalable, enterprise-grade data solutions ...

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 ...

For years, companies have been moving their most valuable customer data into countless different systems used by marketing, ...

Data scientists today face a perfect storm: an explosion of inconsistent, unstructured, multimodal data scattered across silos – and mounting pressure to turn it into accessible, AI-ready insights.

Over at the Hortonworks Blog, Jim Walker writes that the shift to data-oriented business is happening everywhere. An as many enterprises are learning, interoperability is the key to building their Big ...