- Meet the secret weapon that declutters my desk and cools my laptop in one go
- Quantum computing gets an error-correction boost from AI innovation
- Don't sleep on this TCL TV in 2025: This new Mini LED model gives OLED a close fight
- I wore Whoop's latest health tracker - it gave me the best of Oura Ring, Apple Watch, and more
- CDO and CAIO roles might have a built-in expiration date
Trade routes of the digital age: How data gravity shapes cloud strategy

Every strategic decision, from customer engagement to AI-driven automation, relies on an organization’s ability to manage, process and move vast amounts of information efficiently. However, as companies expand their operations and adopt multi-cloud architectures, they are faced with an invisible but powerful challenge: Data gravity.
Data gravity is a term coined by Dave McCrory in 2010 to describe the tendency of large datasets to attract applications, services and even more data, making them increasingly difficult and costly to move. Just as celestial bodies exert gravitational pull, keeping objects in orbit around them, data exerts a similar force in cloud computing. Once data reaches a critical mass within a given platform or region, it becomes a magnet for computing workloads, applications and analytics services, creating a self-reinforcing cycle — just like cities along the Silk Road pulled in traders, wealth and innovation.
This gravitational effect presents a paradox for IT leaders. While centralizing data can improve performance and security, it can also lead to inefficiencies, increased costs and limitations on cloud mobility. Organizations that fail to account for data gravity risk being trapped in a single cloud provider’s ecosystem, incurring high egress fees, experiencing latency issues and struggling with compliance requirements. Those who manage it strategically, however, can turn data gravity into a competitive advantage, using it to enhance performance, security and agility across a distributed cloud infrastructure.