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

This presentation provides an overview of big data analysis, including its history, challenges, and techniques. It explains the characteristics of big data, such as volume, variety, velocity, veracity, and value. Additionally, it discusses how big data technology can support businesses, with examples such as better decision-making, product re-development, data safety, customer dialogue, automation, and asset optimization.

History on big Data
Big data is a sort of information which is massive, brief
and complex. In ordinary times, there was trouble in
handling the information without the innovation. This
report contains the fundamental idea of big data and
elements of the big data. There are a few difficulties
which expect to be settled for better working of the large
information innovation. Lately, there are not many
procedures which are useful in examining the
information. The new innovation of large information
helps in supporting the business which works on the
benefit of the business.
Information Systems and Big Data Analysis
What is big Data
Big data is a term used to suggest the huge measure of information utilized
by information investigators to reach at a specific resolution. The information
is extremely huge which makes issue in its handling, sorting out and
interpreting. The information can be gathered from different sources, for
example, online entertainment locales, perceptions and records. There are a
few attributes of huge information which can be made sense of as given
beneath:
• Volume
• Variety
• Velocity
• Veracity
• Value
Characteristics of Big data
Volume: The Big data comprises of different information which
is enormous in size. .
Variety: The information has a distinctive sort, for example,
organized, semi organized and unstructured.
Velocity: This term mentions to the speed of the information at
which it is made or created.
Veracity: This term indicates to the honesty of the information.
Value: The significant worth of enormous information comes
from the viable activities, solid client connections and a few
business benefits in evaluating connections.
The challenges of big data
analytics
There are various challenges which are faced by the big data
analytic which can be elaborated as given below-
• Scarcity of knowledge specialists
• Incorporating information from different sources
• Information development issues
• Absence of appropriate comprehension of large
information
References
Lee, M., Lee, S.A. and Koh, Y., 2019. Multisensory experience
for enhancing hotel guest experience: Empirical evidence from
big data analytics. International Journal of Contemporary
Hospitality Management.
Liu, X., Sun, R., Wang, S. and Wu, Y.J., 2020. The research
landscape of big data: A bibliometric analysis. Library Hi Tech.
How Big Data technology could
support business & Examples
• Settling on better business choices
• Re-development of products
• Data safety
• Dialogue with clients
• Automation
• Ideal usage of assets
Techniques that are currently
available to analysis big data
According to the report of Mckinsey, there are a few procedures utilized by
the enormous partnerships to tackle the issue of the huge and heterogeneous
information. The various methods utilized in enormous information are made
sense of as given beneath:
A/B testing
Machine learning
Statistics
Natural language processing
Data mining