Principles of Business Analytics

Principles of Business Analytics
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TABLE OF CONTENTS
Task 01..................................................................................................................................................1
Introduction.......................................................................................................................................1
Usage of Business Analytics..............................................................................................................2
Data Mining Process..........................................................................................................................3
Comparison with Business Intelligence & Challenges......................................................................4
Conclusion.........................................................................................................................................5
Task 02..................................................................................................................................................5
Introduction.......................................................................................................................................5
Task 2.01...........................................................................................................................................6
Task 02.2.........................................................................................................................................10
Task 02.3 (Conclusion)....................................................................................................................12
References...........................................................................................................................................13
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Task 01
Introduction
Business analytics may be defined as the underlying technologies, skills and practices meant for past
business performance investigation coupled with exploration using iterative process with the objective
of gaining insight with regards to future performance of business and aid in planning process. It is
noteworthy that while business analytics does refer to past performance but it is primarily with the
objective of gaining understanding of future business performance. This process requires extensive
use of statistical techniques which include both predictive and exploratory modelling. The objective
of this report is to highlight the highlight the utility of business analytics in various fields,
distinguishing it from business intelligence and highlighting the underlying challenges involved in
using both data mining and business analytics.
Usage of Business Analytics
Business analytics has four main types of tools namely descriptive, predictive, prescriptive and
exploratory analytics. Descriptive analytics tends to aim at gaining insight with regards to historical
data and thereby aims to summarise the historical data in order to derive key learning. The focus of
the predictive analytics is to deploy statistical tools related to predictive modelling so as to derive
future predictions. Prescriptive analytics as the name suggests tends to deploy tools such as
simulations and optimisation techniques in order to outline the best possible decision. Exploratory
analytics tends to focus on exploring using various models so as to enhance understanding which can
be further used.
A particular usage of predictive analytics is being made by online retailers to identify the potential site
path which is more likely to lead to sale or abandoning of cart. The customer navigation data is used
in this regards. Descriptive analytics tool are quite useful in analysing stock behaviour by referring to
the empirical performance of the stock. Besides, in order to decide on the product price, prescriptive
analytics tools are used using various market variables. A key application of business analytics may
be observed in enhancing supply chain efficiency by managing inventory so as to avoid excess
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inventory which tends to bring significant savings in terms of ordering and storage costs associated
with inventory. An example of a company in this regards is Pepsi Co (Orem, 2016).
An example of company which is using data analytics for customer retention and acquisition is Coca
Cola which collects regular feedback from customers and then uses the same for product development
using business analytics (BA) tools. Another company which relies on BA tools is Netflix which
sends targeted advertisements to the subscribers based on the past viewing pattern and also the search
pattern. This results in better customer service and enhance the satisfaction of the customers. Various
financial institutions tend to deploy BA as a risk management tool. An example in this regards is
Singapore based UOB Bank which tends to carry real time analysis using the input data for
determining the value at risk which enables the bank to take requisite measures for managing risks.
Amazon tends to use BA for driving innovation in the whole foods segment. By focusing on the
pattern of customers busying grocery and the customer behaviour with regards to suppliers, the
company is able to understand the loopholes that are present and exploit the same to push new and
innovative products (Kopanakis, nd).
Data Mining Process
The various steps involved in the CRISP-DM methodology are highlighted in the following diagram.
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