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 results are in! This comprehensive study tracks enterprise adoption rates and maturity across key architectural patterns - from cloud data warehouses and real-time analytics to data lakehouses, ...

Why modern observability systems fail during incidents, and how new architectures fix them.

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, ...

In today’s enterprise environments, data no longer functions as a record of what has happened. It operates as a live substrate through which decisions are executed, policies are enforced, and ...

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 ...

As organizations scale their AI and analytics efforts, a data architecture that is “up to snuff” is even more critical to business success. Data teams are being asked to deliver faster insights, ...

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 ...

In the current landscape of pervasive connectivity, data has become an indispensable asset for enterprises, particularly within the automotive sector. According to a 2019 McKinsey & Company report, ...