Chloe Maraina builds value from complexity. As a Business Intelligence expert with a strong data science streak, she’s spent years turning sprawling enterprise data estates into living, breathing decision systems. Her focus is converged analytics—unifying transactional, analytical, and streaming
Boardrooms buzzed about generative breakthroughs, yet a colder reality surfaced as a new survey found that the majority of enterprises still cannot move data freely enough to feed the very models they hope will transform the business. That tension between ambition and access set the stakes: growth
Operational missteps in aviation rarely stem from a lack of data; they arise when flight events, maintenance actions, and parts movements live in silos that resist timely reconciliation and leave crews guessing at the truth on the ramp. When a flight logbook update must traverse email chains before
For the first time at true hyperscale, a social platform’s AI backbone is being rebuilt around commodity-efficient Arm CPUs to orchestrate billions of agentic interactions while GPUs and custom accelerators focus on raw parallel compute. Meta’s agreement to deploy tens of millions of AWS Graviton5
The moment agents stopped asking for dashboards and started filing tickets, shipping code, and adjusting prices, the quiet plumbing of data platforms became the frontline that decided whether automation saved money or broke production. Enterprises that once tolerated stale extracts and fragmented
The race to deploy generative intelligence has reached a fever pitch, yet most enterprise architectures are currently struggling to keep pace with the sheer volume of high-velocity data required for autonomous decision-making. In the current corporate landscape, the transition from traditional data
