Big Data

Big Data exceeds the reach of commonly used hardware environments and software tools, to capture, manage, and process it within a tolerable elapsed time for its user population” (Merv, 2011)

Big Data refers to data sets whose size is beyond the ability of typical database software tools to capture, store, manage and analyze” (McKinsey Global Institute, 2011)

Big data refers to collected data sets that are so large and complex that they require new technologies, such as artificial intelligence, to process. The data comes from many different sources. Often they are of the same type, for example, GPS data from millions of mobile phones is used to mitigate traffic jams; but it can also be a combination, such as health records and patients' app use. Technology enables this data to be collected very fast, in near real time, and get analyzed to get new insights (European Parliament, 2021).

Big Data is different from traditional data sources:

1.      Big Data is often automatically generated by a machine

2.      Is typically an entirely new source of data.

3.      Many Big Data sources are not designed to be friendly (Franks 2012, p9).

 

European Parliament (2021). Big Data: definitions, benefits, challenges (infographics). https://www.europarl.europa.eu/news/en/headlines/society/20210211STO97614/big-data-definition-benefits-challenges-infographics

Franks, B. (2012). Taming the Big Data Tidal Wave. Hoboken, NJ: Wiley

Merv, A. (2011). Big Data. Teradata Magazine, 1 (11)

McKinsey Global Institute (2011). Big Data: the next frontier for innovation, competition, and productivity, May 2011


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