Modern Data Architecture (MDA) fills the gaps left by traditional data architecture so enterprises can reduce time-to-insight as their data scales and data consumer demands multiply.
An MDA approach is designed to make it as easy as possible for data analysts, developers, model builders and even robotic "digital workers" to get decision-quality data in whatever form helps them the most. But MDA is not a switch you flip or a thing you buy, and success is much less likely without careful planning.
Investing in MDA is a complex undertaking that calls for new ways of working: new components, new capabilities, new skills, a new operating model and even a new mindset. If done well, there's a huge payoff to reducing friction between data producers and data consumers; if not, one may end up with slow performance, disappointed users, failed pipelines or runaway storage costs.
You'll learn about the importance of: