Intelligent CIO Europe Issue 49 - Page 56

FEATURE : DATA MANAGEMENT

THRIVING AND SURVIVING IN TODAY ’ S INCREASINGLY COMPLEX AND VOLATILE WORLD CALLS FOR A NEW DATA MANAGEMENT ARCHITECTURE .

Put simply , a Data Fabric is a single environment consisting of a unified architecture and services that helps organisations manage and maximise the value of their data , by eliminating data silos and simplifying access to multiple data assets across the entire business on demand , making it faster and easier to gain new insights and undertake real-time analytics .
The good news is that as an overlay to existing legacy applications and data , the Data Fabric enables organisations to maximise value from their existing data lakes and data warehouses . There is no need to rip-and-replace any existing technology investment .
Born out of the pressing need to find a better way to handle enterprise data , a Data Fabric utilises analytics over existing and discoverable metadata assets to support the design , deployment and utilisation of integrated and reusable data across all environments .
According to Gartner , there are four key attributes of a Data Fabric architecture : it must collect and analyse all forms of metadata including technical , business , operational and social ; it must convert passive metadata to active metadata for frictionless sharing of data ; it must create and curate knowledge graphs that enable users to derive business value ; and it must have a robust data integration backbone that supports all types of data users .
So , what are the key components of a Data Fabric ?
Key architectural components : An overview
Consisting of multiple components , data flows and processes that must all be coordinated and integrated , the Data Fabric analytics architecture features a complex array of technologies and functions . These include :
• A real-time analysis ( RT ) platform – The first analytical component that analyses streams of data ( transactions , IoT streams , etc .) coming into the enterprise in real-time .
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