Big Data Case Study
Breaking Down Of Big Data (the 3Vs) The big data that comes in such voluminous size is derived from diverse sources such as sales record of a business, company or organization, gathered results of an experiment either scientific or the social one or the real-time sensors applied in the internet of things. This data may be available in raw form or in partially processed form using separate software tools before the data is finally analyzed. The same data may exist in various forms of file types such as structured data available in form of SQL database stores, unorganized data such as document files, and data streamed directly from the sensors. In addition to that, the big data may involve one from various multiple sources that have been integrated and accumulated together.
For instance, an analytics sifting through the big data with the aim of gauging and evaluating the success and future standing of a company may do so by comparing sales data of past few years, return data given by the customers and reviews left in the online platforms after the clients have bought the product. Such a public computing can accumulate petabytes of data and scale up hundreds of servers and ensure the successful completion of the process of analyzing the big data. This system is also cost effective as an organization can pay for the storage and after completion of the process of analytics it turned off until any other time it will be required again. Application of Big Data in Organizations Cloud Computing Big data has spanned the growth of cloud computing.
In defining cloud computing using simple terms, it is the process of storing and accessing programs and data routed over the Internet instead of the normal computer storage in the hard drive. The cloud is just an allegory for the Internet (Kempe, 2015). This process was slower some few years back due to slow and sluggish pace in accessing the data maintained. This concept has been in use for a period, even before the eras of 1950s, and organizations used them to uncover the emerging issues and trends Big data has therefore enabled the various organizations to perform data analytics in variety of ways. Each industry applies data analytic to enhance its capability of delivering unique services and products to their customers (Ankam, 2016).
In the hospitality and travel industry, keeping the incoming customers happy is the key secret in unlocking their potential. Therefore, customer satisfaction is paramount but at the same time difficult to gauge. For instance, people moving around the world to execute various businesses activities will not need to carry the necessary documentation in hard copies but they require to save them in the cloud and later access them when needed regardless of the location of the user. The other future trend between cloud computing and big data will be on speed where data processing will be faster and expedited due to its availability from a closer source and therefore accelerate the whole process of processing and computation. This will enable swiftness in the real-time processing of data and quickens the process of decision-making and service delivery, in areas that rely on big data analytics (Ruparelia, & MIT Press, 2016).
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