Information Systems and Big Data Analysis

This presentation covers the basics of big data, its characteristics, and techniques for analysis. It also discusses the challenges in big data analytics and how big data technology can support businesses with examples. The presentation is relevant for students studying Information Systems and Big Data Analysis.

History on big Data
Big data refers to the data which is being
generated across the world wide at the
unprecedented rate. It is a combination of all
tools and processes related to managing and
utilize large data sets.
Information Systems and Big Data Analysis
Name of the Student
What is big Data
Big data is refer to collection of the data that is vast in
volume, yet growing exponentially with the time. Big
data are large in size and complex that none of the
traditional data management tool can store it and process
it efficiently.
Characteristics of Big data
The big data can be delineated by some
characteristics which are mentioned below:
Volume
Variety
Velocity
Value
The challenges of big data
analytics
The data is a valuable asset for every
organisation. Big data and analytics are still in
initial stage of its growth, its importance can not
be undervalued. There are various challenges of
the big data analytics which are mentioned
below:
Big data talent gap
Uncertainty of the data management
landscape
Long system response time
Expensive maintenance
References
Riley, C., Vrbka, J. and Rowland, Z., 2021. Internet of things-enabled sustainability, big data-driven decision-
making processes, and digitized mass production in Industry 4.0-based manufacturing systems. J. Self-Gov.
Manag. Econ, 9, pp.42-52.
How Big Data
technology could
support business &
Examples
• Making better business decision
• Understanding customers
• Automation-
• Promote cost saving measures
Techniques that are currently
available to analysis big data
Data analytics is a process to examine the data sets and
drawing a conclusion about an information that they
contain, commonly through a specific system methods
and software. technologies of data analytics are used on
industrial scale and in all commercial business industries.
These techniques are mentioned below:
A/B testing-
Data mining
Machine learning
Data fusion and data integration