There’s a wide range of reasons why many organizations are deciding to modernize their data architectures. But they all agree on one thing: by using data more effectively, more widely, and more deeply, they can improve and optimize business and decision-making processes that will help them stay competitive in the emerging digital economy.
To prepare data architectures for the next evolution of analytics, the current systems that rely on physical data movement and redundant data storage, must be modernized. However, for it to be effective, modernization must be seamless and must not disturb current and ongoing business processes.
This whitepaper describes how data virtualization can help to modernize an existing data architecture to unlock and exploit all the existing data more quickly, to present more low latency data, and to support new forms of data usage, such as data science, without the need to mass replace existing tools.