History and Characteristics of Big Data: Information Systems and Big Data Analysis

This presentation covers the history of big data, including its first trace in 1663, and defines big data as extremely large sets of data that can be analyzed computationally to reveal patterns and trends. The presentation also discusses the characteristics of big data, including volume, variety, velocity, value, and veracity. Techniques available for businesses to analyze big data, such as regression analysis, factor analysis, and associate rule learning, are also covered. Examples of big data technology supporting businesses, such as Sainsbury's, are provided, as well as challenges faced in big data analytics, including a lack of knowledge experts, data growth issues, and confusion in selecting big data analytics tools.

History on big Data
In the year 1663, first trace of big data was
seen at the time when John Graunt dealt with
devastating sums of information when
studying bubonic plague that was haunting
Europe at durations.
Information Systems and Big Data Analysis
What is big Data
Big data is said to extremely large sets of data
which may be analysed in computational
manner for revealing patterns and trends
concerned with human behaviour as well as
interactions.
Characteristics of Big data
Some features of big data are mentioned below:
Volume
Variety
Velocity
Value
Veracity
The challenges of big data
analytics
In a company, some of challenges faced in big
data analytics are as follows:
Lack of knowledge experts
Data growth issues
Confusion in selecting bid data analytics tool
References
Choi, T. M., Wallace, S. W. and Wang, Y., 2018.
Big data analytics in operations
management. Production and Operations
Management. 27(10). pp.1868-1883.
How Big Data technology
could support business &
Examples
For example, managers of Sainsbury's use these
big data analytics in their operations which aid
them in enhance their productive level.
Techniques that are currently
available to analysis big data
Mentioned below are certain techniques that are presently
available for businesses to analyse available big data:
Regression analysis
Factor analysis
Associate rule learning