Big Data Management

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Big Data Management, structured data, semi-structured data, unstructured data, sources of unstructured data, examples of unstructured data.

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Surname 1Name:Course:Tutor:Date:Big Data ManagementQuestion 1Technology has underscored big data management in many ways. For instance, throughtechnology-enabled computing, significant volumes of both unstructured and structured data arequickly organized, administered and governed effectively. This technology, however, facilitatesbig data managements aim to deliver high-quality data and accessibility for enterpriseintelligence and applications that analyze this data. In distributed systems, a networkcommunicates and coordinates the systems components functioning by messages. All thenetworked hardware and software function with the aim of a particular objective. Thence, bigdata management is underscored by the implementation of its dissimilar policies to theadministering, organizing and governing of unstructured and semi-structured (Inmon & Anthony,P. 26-27)Question 2Latency refers to the hold up from the input into a system to expected outcome. It varies fromone system to the other. Low latency is significant for big data management because it enhancesquick and efficient moving of data across the businesses networks. The demand for low latencyhas gone
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