Volumes: The volume of big data exceeds “normal” dimensions, usually amounting to several terabytes it can even push into the petabyte range, depending on the data at hand.What makes big data challenging from a data management perspective are the following three factors: The aim is to identify hidden systematic patterns, correlations and interrelations from which decision-relevant information, optimisation potential and – where possible – sustained competitive advantages can be obtained.įigure 2: Big data analytics funnel – from big data to meaningful resultsĪs can be seen from Figure 2, big data input can consist of various data forms and can come from different sources, e.g. Forecasting the sale of ice cream in the supermarket based on weather forecasts and historical sales data monitoring the spread of diseases based on search volumes predicting the need for repair of aircraft engines in real time – the possible uses and potential of big data analytics are undeniably inspiring.įigure 1: Overview of typical applications of big dataīut what is really behind this alleged “crystal ball”? Big data analytics is the study of large quantities of data using various statistical analysis methods.
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