Analyzing Big Data: Information Systems, Challenges & Technologies

This report provides an overview of big data within the context of information systems, highlighting its assimilation for corporate decision-making. It discusses the nature and features of big data, including its volume, velocity, variety, and veracity. The report identifies key challenges in big data analytics, such as a specialist's deficiency, data growth issues, data security concerns, and the complexity of data instrument selection. It also outlines techniques currently available for big data analysis, including data mining and data integration. Furthermore, the report explores how big data technology supports businesses through facilitated decision-making, improved consumer understanding, and automation, referencing examples and academic sources to support its analysis. Desklib offers a platform to explore similar solved assignments and study resources.

History on big Data
Big data is an assimilation of the information that is
stores for making decisions for the corporations. The data
is collect by the using the transmissible application
utilizing the electric signals so that is will be helpful for
the company in storing the information in the computer
systems. These data are used by the corporation for
modifying the different functions for giving better
customer experiences. It assists the firm in increases their
net turnover which ultimately leads to increase in the
productivity and profitability of the firm (Choi, Wallace
and Wang, 2018). In the following report, the concept of
big data and the nature and features of it are explained.
With considering the big data, the challenges that he
organization face during the analysis of the big data is
described by explaining the techniques of evaluation for
the big data. Moreover, the technology which is used for
supporting the firms.
Information Systems and Big Data Analysis
Name of the Student
What is big Data
The big data is a termed which is used to define the assimilation of
information on a vast rage which is very problematic to do analyses
and evaluate the data. The data which the firm collects can be
structures and unstructured as well. So, for this it is not possible for
any human to complete and analyze the whole data. For this,
various technologies are developed to sort the information. The
traditional software for analyzing the tools are not as much
efficient is analyzing such a huge data. To automatically track and
store the data these new applications are developed. This helps the
professionals a knowledge and ability to evaluate the information
in the right order.
Characteristics of Big data
1. Velocity
2. Veracity
3. Volume
4. Variety
The challenges of big data
analytics
• A specialist's deficiency Expertise
• Data Growth Issue
• Data Security
• Deficiency of considerate of the Big data
• Data instrument choice and ambiguity
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.
Côrte-Real, N., Ruivo, P. and Oliveira, T., 2020.
Leveraging internet of things and big data analytics
initiatives in European and American firms: Is data
quality a way to extract business value?. Information &
Management, 57(1), p.103141.
How Big Data
technology could
support business &
Examples
• Facilitate decision-making
• Improved consumer understanding
• Automation
Techniques that are currently
available to analysis big data
• Data Mining
• Data Integration
• A/B Testing