Intelligent Data Centres Issue 1 - Page 59

UNCOVERING THE LAYERS manage, secure, govern and protect data along with tools to enable the consumption of data by a broad set of applications and tools. The complexity of data is handled based on defined policies that span across locations, hardware infrastructures from on-premises to the cloud to the edge and containers. Pinakin Patel, Head of Solutions Engineering at MapR delivery between sources and destination to allow enterprises to focus solely on the use case and not the plumbing. Beyond storage Unlike the old world of storage that centred around volumes, blocks, files and more recently objects, dataware instead presents a set of standards- based APIs that enables enterprises to The notion of abstraction is like the way in which operating systems manage hardware using device drivers that provide a known set of interfaces to mask the complexity of the underlying graphics, networking and audio chipsets. This capability to deliver data based on need instead of underlying limitation is particularly useful in use cases that may require multiple sources of data, of differing types, that are served from disparate sources. For example, take a ride sharing service such as Uber or Lyft; the service will include both real-time streaming data from drivers and passengers, traditional customer information from a database and, in the back end, the service is making lots of analytical decisions around journey planning, capacity and demand. Factors such as weather, time of day and temperature can all add into these calculations. There may be multiple sources for these elements and differing parsing that may change as the application set evolves. Hard coding these data elements into the workflow is inefficient, especially if the data structure, type or source changes. Instead, in a dataware model, the dataware abstraction layer manages acquisition, storage, parsing and delivery of the required data to the application and handles any return path data capture. If a new data type is required for the applications, for example geographic information system (GIS) mapping data, the dataware can handle the management complexity involved in its acquisition and present the data to the application group in the required format. Although the term ‘dataware’ might be new, the notion of abstraction is very old and as more data technologies start to coalesce around emerging standards such as JSON, S3, Spark, Kafka and others, the easier it becomes to add Issue 01 59