Analyzing Data Analytics Use for Business Value in Organizations

This report investigates the role of big data analytics in providing business value to organizations. It aims to identify factors that add value and critically analyze the role of big data analytics in business, as well as the challenges faced by organizations. The literature review highlights the increasing volume, variety, and speed of data and its potential as a valuable resource. Research methodology includes positivism philosophy, deductive approach, and descriptive design, with a sample size of 65 business managers. The study references various works on big data computing, social science, and decision support systems.

USE OF DATA ANALYTICS IN
PROVIDING BUSINESS VALUE TO
ORGANIZATIONS

Introduction
 Big data analytics programming is intended to work with huge
information stages, which incorporate Hadoop bunches worked around
ware servers and versatile conveyed stockpiling, NoSQL database
frameworks and concentrated elite investigation databases. The
instruments bolster prescient demonstrating and information mining
strategies and are fit for scaling as more information is fused into
explanatory models. Dealing with the numerous items delegated
enormous information investigation programming can settle on your
purchasing choice considerably more troublesome, as the usefulness,
highlights and capacities of these apparatuses are frequently
comparative.

Aims and objectives
 The research will have aims to investigate the role of big data analytics
in business intelligence,
 Additionally, objectives of the research can be explained as followed.
 To find out the factors that can add value in business of an organization
 To critically analyze the role of big data analytics in business of an
organization
 To analyzes the challenges faced by the organization in using big data
analytics

Literature review
Role of big data analytics in business
 The heightening volume, assortment, and speed of data that is being
produced today can give organizations numerous basic difficulties.
 Be that as it may, this excess of data can likewise be an essential
resource for those associations that pick to gain by it.
 Capable huge information and investigation arrangements are
presently being utilized to examine this blast of data and in a general
sense change the way that associations oversee their every day
operations.
 The preferences to be picked up from huge information and
examination are generous. Associations that are forcefully seeking
after examination what's more, data procedures are separating
themselves from their opposition

Contd.
 Sixty-three percent of respondents revealed that the utilization of data—
including huge information and examination—is making a upper hand
for their associations
 When contrasted with organizations that depend on customary
investigation alone, associations that executed huge information and
examination pilot tasks or organizations are 15 percent more prone to
report a huge favorable position from their data resources and analytics
 Moreover, the IBM Institute of Business Value additionally found that 75
percent of pioneers refer to development as the key wellspring of
significant worth from analytics (Assunção et al. 2015).

Research Methodology
 In the present paper, point by point inquire about method for
investigating the part of data innovation in enrollment arrangement of
medicinal services association has been utilized.
 Chosen look into rationality is positivism, which can help to acquire
data in view of proper rationale and also assessment.
 Likewise, deductive approach will enable the analyst to lead the
investigation in view of optional sources in beginning stage.
 Descriptive design will help the analyst with a specific end goal to
characterize the utilized and also connected ideas in point by point way
that aids request to characterize the effect of data innovation on
enlistment framework in human services association.
 Sample size for the research will be taken as 65 managers of business
organization.

References
 Assunção, M. D., Calheiros, R. N., Bianchi, S., Netto, M. A., & Buyya,
R. (2015). Big Data computing and clouds: Trends and future
directions. Journal of Parallel and Distributed Computing, 79, 3-15.
 Brinkmann, S. (2014). Interview. In Encyclopedia of Critical
Psychology (pp. 1008-1010). Springer New York.
 Chang, R. M., Kauffman, R. J., & Kwon, Y. (2014). Understanding the
paradigm shift to computational social science in the presence of big
data. Decision Support Systems, 63, 67-80.
 Demirkan, H., & Delen, D. (2013). Leveraging the capabilities of
service-oriented decision support systems: Putting analytics and big data
in cloud. Decision Support Systems, 55(1), 412-421.
 Flick, U. (2015). Introducing research methodology: A beginner's guide
to doing a research project. Sage.