Risk Analysis of Using Big Data in Computer Sciences | Zendy

Jesus Silva | Zendy; Omar Bonerge Píneda Lezama | Zendy; Ligia Romero | Zendy; Darwin Solano | Zendy; Claudia Nélida Fernández | Zendy

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Risk Analysis of Using Big Data in Computer Sciences

Author(s) -

Jesus Silva,

Omar Bonerge Píneda Lezama,

Ligia Romero,

Darwin Solano,

Claudia Nélida Fernández

Publication year - 2019

Publication title -

procedia computer science

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 0.334

H-Index - 76

ISSN - 1877-0509

DOI - 10.1016/j.procs.2019.11.052

Subject(s) - big data , computer science , data science , enthusiasm , data warehouse , analytics , data quality , quality (philosophy) , data analysis , database , data mining , business , psychology , social psychology , metric (unit) , philosophy , epistemology , marketing

Today, as technologies mature and people are encouraged to contribute data to organizations’ databases, more transactions are being captured than ever before. Meanwhile, improvements in data storage technologies have made the cost of evaluating, selecting, and destroying legacy data considerably greater than simply letting it accumulate. On the one hand, the excess of stored data has considerably increased the opportunities to interrelate and analyze them, while the moderate enthusiasm generated by data warehousing and data mining in the 1990s has been replaced by a rampant euphoria about big data and data analytics. But, is this as wonderful as seems? This paper presents a risk analysis of Big Data and Big Data Analytics based on a review of quality factors.

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