Big Data Challenges - Definition, Characteristics and Technologies
Keywords:
Data lake, Big data, HadoopAbstract
Volume, complexity, variety and velocity of generated data today reach incredible levels and data cannot be collected, selected, processed or managed through widely used and applied software tools. The need to extract meaningful information from big data evokes the development of new approaches and technologies for storing, processing and analyzing big data coming from different sources. This paper aims to present the definition, characteristics and technologies for storing and managing big data that require a new approach to understanding data and information.References
@Louis_Ashworth (2018). Who is Dr Aleksandr Kogan, the Cambridge academic accused of misusing Facebook data?. DOI: https://www.varsity.co.uk/news/15192
JS Hurwitz, A Nugent, F Halper, M Kaufman (2013). Big data for dummies. For Dummies. URL: https://books.google.com/books?hl=en&lr=&id=XPkAEFXo7VgC&oi=fnd&pg=PA1&dq=Big+Data+For+Dummies+Hurwitz&ots=KQFkqWnhpm&sig=t8YKnhj-qK5HUWfr6HqziV4PEd4
Irene Mikhailouskaya (Makaranka) (2019). Data Lake Implementation: 2 Alternative Approaches. DOI: https://www.scnsoft.com/data/data-lake-implementation-approaches
J Manyika, M Chui, B Brown, J Bughin, R Dobbs… (2011). Big data: The next frontier for innovation, competition, and productivity. URL: https://www.mckinsey.com/capabilities/tech-and-ai/our-insights/big-data-the-next-frontier-for-innovation.pdf (accessed 2019-02-10)
Tom Shafer (2018). The 42 V's of Big Data and Data Science. DOI: https://www.elderresearch.com/blog/the-42-vs-of-big-data-and-data-science/
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Copyright (c) 2019 Stanimira Yordanova, Kamelia Stefanova (Author)

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