Incorporation of Data Analytics Assesment

Running head: INCORPORATION OF DATA ANALYTICS
Incorporation of data analytics
Name of the Student
Name of the University
Author Note

INCORPORATION OF DATA ANALYTICS
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Table of Contents
Abstract......................................................................................................................................2
Research approach and methodology.........................................................................................2
Detailed description of the significant identified trend..............................................................3
Challenges..................................................................................................................................6
Opportunity................................................................................................................................7
Considerations............................................................................................................................8
Impact of the trend on business analytics practise.....................................................................8
Conclusion................................................................................................................................10
References................................................................................................................................11

INCORPORATION OF DATA ANALYTICS
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Abstract
Digital transformation is one of the top trends which are followed in the business system
analysis; as a result, the performance of the agile teams has enhanced to a significant extent.
New-age technologies like data analytics and cloud computing have taken over in every
disruptive business environment. Each of these trends was very much useful to enhance the
skill of the workforces, which are working with diverse categories of business systems such
as the payroll business system and personnel business system.
However, there are numerous challenges, opportunities, and other considerations that are
associated with the use of these emerging trends, which will be evaluated in this report from
the perspective of the scholars who have stated their opinion about the implications of the
emerging trends in the business system analysis. The impact of the selected trend shall also
be discussed in the concluding sections of this report.
Research approach and methodology
Secondary data collection method shall be considered in this report where data will be
collected from a reputed and reliable secondary data source, which is Google Scholar. Data
shall be connected from peer-reviewed journals where scholars have stated their opinions
about the selected topic of this report. The project management journals shall be considered
in this report as it will be very much useful to understand the impact of the emerging trends
from the perspective of a system analyst. All the peer-reviewed journals that will be
considered in this report have been published in the last five years to avoid any sort of
outdated data, as the business conditions of the disruptive business environment are very
much dynamic. Maintaining the integrity of the data which will be collected from the
secondary sources is the only ethical consideration of the research methodology of this report.

INCORPORATION OF DATA ANALYTICS
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Detailed description of the significant identified trend
There are numerous challenges which are faced across business organisations all over the
world; understanding the business requirement is the prime challenge faced by the systems
analyst of those organizations.
The emerging trend which is selected for this research is Data Analytics (DA), a different
perspective of this trend shall be evaluated from the perspective of scholars. Digital
transformation is ensured in a business that makes the most out of DA tools, which can help
them to have control of their raw data (Grove et al. 2018). The technical capabilities of all the
resources working with the business system can be improved due to the use of DA tools. Data
and analytics investment is one of the emerging trends of any business which likes to work
with advanced business systems (Alsheikh, Niyato, Lin, S., Tan & Han, 2016). The
deployment of DA tools has helped commercial establishments to protect the integrity of
their raw data in a systemized modus (Nastic, Rausch, Scekic, Dustdar, Gusev, 2017).
Decision-making capabilities of the business systems have improved to a huge extent, and it
is mainly due to the use of DA tools. There are diverse categories of DA procedures that are
used in business systems such as descriptive analytics, diagnostic analysis, predictive
analysis, and prescriptive analysis.
According to Mikalef et al. (2018), data mining and data clustering are directly associated
with DA and each of these are very beneficial to reduce the computational errors of the
business systems. The DA tools are very much significant in maintaining the strategic goals
of the business systems. On the other hand, as discussed by Verhoef, Kooge & Walk (2016),
cloud infrastructure, which is common for every business system, is maintained with the