İngilizce

Volume is obviously the most common trait of Big Data. Many factors contributed to the exponential increase in data volume, such as transaction-based data stored through the years, text data constantly streaming in from social media, increasing amounts of sensor data being collected, automatically generated RFID and GPS data, and so on. In the past, excessive data volume created storage issues, both technical and financial. But with today’s advanced technologies coupled with decreasing storage costs, these issues are no longer significant; instead, other issues have emerged, including how to determine relevance amid the large volumes of data and how to create value from data that is deemed to be relevant.

Norveçce

Volum er åpenbart den vanligste egenskapen til Big Data. Mange faktorer bidro til den eksponensielle økningen i datavolum, for eksempel transaksjonsbaserte data lagret gjennom årene, tekstdata som kontinuerlig strømmer inn fra sosiale medier, økende mengder sensordata som samles inn, automatisk genererte RFID- og GPS-data, og så videre. Tidligere skapte overdreven datavolum lagringsproblemer, både tekniske og økonomiske. Men med dagens avanserte teknologier kombinert med reduserende lagringskostnader, er disse problemene ikke lenger viktige; i stedet har andre problemer dukket opp, inkludert hvordan man kan bestemme relevans blant de store datamengdene og hvordan man kan skape verdi ut fra data som anses å være relevante.

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İngilizce
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