Intelligent Data Centres Issue 01 | Page 60

UNCOVERING THE LAYERS additional data types and data processes into a dataware layer. AI and security Currently the use case most relevant for dataware is within the area of Artificial Intelligence. For the concept to take off, the current generation of pioneers are in the process of creating and testing models to teach machines how to spot events and deal with different situations. This process of Machine Learning is largely dependent on access to lots of data. Dataware is perfect for these types of projects as it can handle almost any type of data with the ability to scale capacity almost infinitely by offloading to the cloud as well as handling requirements such as performance tiering and backup. The other major issue that dataware can potentially help address is security. The present situation where enterprises keep multiple silos of data that typically have separate access, encryption 60 Issue 01 and governance criteria is incredibly difficult to secure. As data starts to move from these individual silos into other areas such as AI research, test and development, the ability to apply controls to ensure security and privacy are made more complex. In a dataware centric model, all data flows through this data abstraction layer which makes it potentially easier to apply policy-based controls at a single point instead of having to fragment the security process. Dataware is an evolving concept and several pioneers in this space, including MapR, are striving to ensure that it supports the widest ecosystem of open standards. This is vital to ensure the technology avoids the proprietary pitfalls of legacy middleware platforms that tended to lock- in customers rather than provide freedom and choice. If these lessons can be learnt and enacted, then it really will be time for a new ware. ◊ DATAWARE IS AN EVOLVING CONCEPT AND SEVERAL PIONEERS IN THIS SPACE, INCLUDING MAPR, ARE STRIVING TO ENSURE THAT IT SUPPORTS THE WIDEST ECOSYSTEM OF OPEN STANDARDS.