[Legacy Report] IEEE Hands-on Metadata Workshop
#Metadata
#Big
#Data
#Dark
#Hyderabad
Metadata is the data that describes data. Just as we would be lost in the world without names and addresses, Big Data would be undiscoverable without fast, efficient ways to manage Metadata, which becomes an imperative in the world of “Big Data†and the cloud. Data engineering leaders now claim that, as more of the data is distributed in the cloud and across the enterprise, the model of holding central databases becomes less relevant, especially for unstructured and semi-structured data. Data Lakes are the new, emerging repositories for such unstructured, distributed Big Data on the cloud. By investigating the metadata, organizations can more quickly and efficiently determine what data needs to be purged and this process can be automated by leveraging metadata automation strategies (Vellante, 2013). About 90% of the Big Data are ‘Dark Data’ – not easily amenable for analysis and insights. Services and products similar to ClipCard are critical to successfully meet the challenges of ‘Dark Data’. Dark Data is the enormous subset of unstructured, undiscovered, untagged information residing within Big Data. Research firm IDC estimates that approximately 90 percent of Big Data is Dark. Dark Data severely challenges the traditional business intelligence and reporting technologies which are struggling to tap the full potential of this new breed of data. New Metadata Management (EMM) tools help address the Dark Data bottleneck, by helping to port, host, manage, search and discover Big Data on Cloud. They help turn Dark Data from warehouse to White Data on Cloud by offering Enterprise Metadata Management (EMM) as a Service.
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