Big Data Analytics: Characteristics, Challenges, and Techniques

This presentation provides an understanding of Big Data analytics, its characteristics, challenges, and techniques that are currently available to analyze big data and how it can support businesses. It includes the history of Big Data, its definition, characteristics, challenges, and techniques such as data fusion and A/B testing. The presentation also discusses how Big Data technology could support businesses and provides examples. References are included at the end.

History on big Data
Big Data analytic provide an endless sources and insight to businesses
which are essential in order to bring improvement in performance and
attain the ability to identify new unrealized opportunists across almost
every industry along with providing assistance in customer personalize.
Reducing risks. Early detection of fraud and internal operation. It assists
an organization to identify its hidden value through the collective data.
The following poster will includes understanding of Big Data analytic
and its characteristics along with its challenges. Moreover, it will include
the techniques that are currently available to analyses big data and how it
can support businesses.
Characteristics of Big data
Volume:
The volume refers to the large amount of data which is collected and
generated by large organization every second.
Variety:
The variety characteristic of Big Data is one of the most crucial element
as it refers to collection of data from various sources and their nature.
What is big Data
Big Data refers to the massive collection of data which is structured
or unstructured. The data may be sourced from customer profile
information, information form serves, order and purchase data,
financial transactions along with search history and employee
records.
The challenges of big data
analytics
Lack of knowledge professionals:
It is important to have skilled and talented professionals in order to
successfully run modern technology and large data tools.
Lack of proper understanding of massive data:
The lack of understanding the data and how its is to be processed,
stored and its overall value has been a challenge for various
organizations.
Data growth issues:
The foremost challenge of Big Data has been the storage of massive
amount of set data and knowledge properly
Techniques that are currently
available to analysis big data
Data fusion and data integration:
This technique focuses on combining set of techniques in order to analyze
and integrate data from multiple sources and solutions.
A/B testing:
This technique involves the comparing of a control group with a variety
of test groups in order to discrete suitable treatment or changes that will
improve a given objective variable.
How Big Data technology
could support business &
Examples
Gain competitive advantage:
The Big Data analysis provides support to organizations by providing
them assistance in understanding where they are lacking relative to this
business operations
Perform risk-analysis:
The Big Data technology support an organization by helping them
determine future and current levels of threats References
• Chauhan, R., Kaur, H. and Chang, V., 2021. An Optimized
Integrated Framework of Big Data Analytics Managing Security
and Privacy in Healthcare Data. Wireless Personal
Communications, 117(1).
• De Santis, F. and D’Onza, G., 2021. Big data and data analytics in
auditing: in search of legitimacy. Meditari Accountancy Research.
Information Systems and Big Data Analysis
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