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Big Data, the name speaks for itself. These are data sets so large, they can no longer be evaluated with conventional technologies because of their size. This is not surprising given that due to the rapid increase in global data volume, the collection, evaluation, and representation of said data has become increasingly difficult. The Zettabyte barrier (1 with 21 zeros; that is 22 digits) was already broken back in 2011. By 2020, this value is likely to climb to 35 Zettabytes1. Managing such enormous data volumes is only feasible with newly developed software. Special functions and techniques allow the simultaneous processing of data records. This concerns the import of entire data records all through to the analysis of different types of information. There is no end to growth in sight, as among other developments, the Internet of Things with its connected devices is a substantial driver of this trend. Big Data’s new dimensions are furthered by the ever-increasing demand from companies. As the number of users grows, expectations are also rising with regards to the timeliness and short-term availability of the data. This means that systems have to perform better in order to handle various tasks simultaneously. Without the ability to successfully manage Big Data, enterprises are no longer able to meet the challenges of the business world. They are considered the losers of global digitalisation. Time is money. Nowadays, this is more relevant than ever.
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1 cf. Michael Gottwald (n.b.)
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