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Big Data Analysis: History, Challenges, Techniques, Characteristics and Business Support

   

Added on  2023-06-18

1 Pages336 Words312 Views
Data Science and Big Data
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History on big Data
Big data has been in use since 1990s. however there is
no clarity about who used this term for the first time buy
most commonly Jhon R. Mashey is given credit for this.
In last few years overall volume of data which is being
used and generated has increased and is mostly used for
decision making process because of which big data has
come into picture.
Information Systems and Big Data Analysis
The challenges of big data
analytics
Data management landscape uncertainty
Big data talent gap
Getting big data into big data platform is another
kind of challenge
Need of synchronization across varied sources of
data
Getting important insights with the help of Big data
analytics
References
Kamilaris, A., Kartakoullis, A. and Prenafeta-Boldú, F.X.,
2017. A review on the practice of big data analysis in
agriculture. Computers and Electronics in Agriculture, 143,
pp.23-37.
How Big Data
technology could
support business
Making better business decisions,
Understanding your customers, Delivering
smarter services or products, Improving
business operations, Generating an income.
Characteristics of Big dataWhat is big Data
Big data is an extremely large dataset which is analysed
conceptually for revelling patterns, associations, trends
identification etc. In other words, it is a large, complex data
set from varied sources that are stored at a single place.
These data sets are of so large quantity that they cannot be
managed by traditional data processing software’s.
Volume: today high volume of data is being stored
exponentially.
Variety: big data provide a feature of storing large and
different variety of data or information together.
Velocity: Big data helps in accommodating large
velocity of data together in an appropriate manner.
Techniques that are currently
available to analysis big data
A/B testing
Data fusion and data integration
Data mining
Machine learning
Natural language processing
Statistics
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