Examining the Advantages of Big Data-Based Decision Making in an Organization

This blog post explores the advantages of implementing big data-based decision making in an organization through the parameters of volume, velocity, and variability. It examines how Tesco uses big data analytics to make better decisions and stay ahead of the competition.

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Contents
Contents...........................................................................................................................................2
Selecting of an organization and using three parameters of volume, velocity and variability to
examine the advantages of implementing big data based decisions making in an organization.....1
REFERENCES................................................................................................................................3

Selecting of an organization and using three parameters of volume, velocity
and variability to examine the advantages of implementing big data based
decisions making in an organization
Big data is said to collection of set of data so large as well as complex which makes it
difficult to process through on hand database management tools along with traditional data
processing applications. It includes challenges such as capturing, transformation, search, storage,
sharing, analysis addition to visualisation (Raut and Et. Al., 2019). Organisation, such as Tesco,
make usage of parameters to devise big data based decisions for making better decisions. For
examination of advantages related to implementing decisions related to big data, use of three
parameters in Tesco are as follows:
Volume: Big data based decisions are concerned with huge volume of data which are being
generated on day to day basis from numerous sources comprising business processes, networks,
social media platforms, machines and so on. In context to Tesco, the advantage gained from
potential to process huge information is major attraction concerned with big data analytics.
Volume presents most immediate challenges to IT structures of company that calls for
distributed approach of querying together with scalable storage. While devising big data based
decisions at Tesco, use of volume benefits in generating data from countless sources as well as in
different formats. Because of rapid production in large sets, the business concern prefers to
incorporate big data in strategies of company in order to substitute traditional methods and
techniques for intelligence along with analytics with custom system which enable in collecting,
storing, processing together with presenting effectively all of data in real time.
Velocity: In a company, data for decision making is required to be generated fast as well as
requires to be processed quickly (Verma, Bhattacharyya and Kumar, 2018). Within Tesco, use of
velocity for big data based decision making benefits increasing rate wherein data flows in the
company with similar patterns of volume. It is examined that use of velocity alert the company
for stocking issues quickly in order to solve issues prior it gets worse. Moreover, it also speeds
up process of decision making of establishment to keep up with changes in the market. It also
supports the company to develop understanding about relative growth of big data along with how
quickly the data reaches to applications, systems addition to users for devising rational decisions.
Variability: In aspect of big data, variability is number of consistencies in data. It is
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inconsistent speed at which big data is encumbered in database. Within Tesco, data is obtained
from ample number of sources, such as, what target audience say on social networks, in house
devices as well as smartphone GPS technology. The significance of sources of information varies
contingent to nature of establishment (Singh, Rathore and Park, 2020). For instance, data related
to mass market product is more aware about social networks against industrial organisations. It is
examined that use of variability in big data decision making at Tesco benefits in taking
unstructured data together with extracting ordered meaning from it. Use of variability gives the
company a way for describing the level in which data sets vary as well as permits in making
usage of statistics for making comparison of own data to that of other data sets.
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REFERENCES
Books and Journals:
Raut, R. D. and Et. Al., 2019. Linking big data analytics and operational sustainability practices
for sustainable business management. Journal of cleaner production. 224. pp.10-24.
Singh, S. K., Rathore, S. and Park, J. H., 2020. Blockiotintelligence: A blockchain-enabled
intelligent IoT architecture with artificial intelligence. Future Generation Computer
Systems. 110. pp.721-743.
Verma, S., Bhattacharyya, S. S. and Kumar, S., 2018. An extension of the technology acceptance
model in the big data analytics system implementation environment. Information
Processing & Management. 54 (5). pp.791-806.
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