The multiple sources, and may have its multiple

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Last updated: March 20, 2019

The data-drivendecision-making process is widely under recognition now these days, and theterm `Big Data’ is on the top most level for running these kind of data-drivendecision-making process. Big data can be derived from multiple sources, and mayhave its multiple formats. It is a high-volume, high-velocity and/orhigh-variety information assets that demand cost-effective, innovative forms ofinformation processing that results insight enhancement, decision-making, and makethe process automatic. High-performanceanalytics lets you do things you never thought about before because the datavolumes were just way too big. For instance, you can get timely insights tomake decisions about fleeting opportunities, get precise answers forhard-to-solve problems and uncover new growth opportunities – all while usingIT resources more effectively.Despite the much laudedpotential, using big data has brought huge challenges in terms of dataacquisition, management, process, storage and analysis.

Big data is unstructured,unlike traditional data in its characteristics of high-volume, high velocity,high-variety of sources and the requirement to integrate all of it foranalysis. Traditional data management and analytical systems are based onrelational and structured database systems. Those systems are not designed forthe huge volume and heterogeneity of big data. Technical Institutions areoperating in an increasingly complex and competitive environment. This paperidentifies contemporary challenges being faced in technical institutions worldwideand explores the potential of Big Data in addressing these challenges.

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Thepaper then outlines a number of opportunities and challenges associated withthe implementation of Big Data in the context of higher education.The paper concludes byoutlining future directions relating to the development and implementation ofan institutional project on Big Data.

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