Data Mining and Visualization for Business Intelligence

Data Mining and Visualization for Business Intelligence
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5th October 2019

Definition of data mining
It is a process by which raw data is turned into useful information (AlOmari & Hassan, 2016).
Data mining finds it application in various fields among them retail, telecommunication,
banking, manufacturing etc.
However, we shall restrict ourselves to retail industry and telecommunications.
 RETAIL INDUSRTRY
Potential benefits of data mining in retail industry.
There are so many benefits of data mining in retail industry.
First, it used in Market basket analysis where natural affinities between two products are
studied.
Apart from this, it is useful in achievement of better customer retention and satisfaction
customer’s need is understood.
Thirdly, it reduces cost of business. When the customer is satisfied, the costs required in
advertising and sales promotion is not incurred thus reduced business costs.
Lastly, it is useful in Customer Relation Management. This leads to improvement quality of
customer service.
The recent developments and why they are exciting;

It helps in Customer retention. Analysis of change in consumption of customer or loyalty is
investigated. Suggestions on the adjustments to be made on pricing and the quality of goods are
then done (Hawkins, 2014).
Besides this designing and constructing data warehouses is the other benefit that come from data
mining in retail industry.
Another recent development is multidimensional analysis of sales, product, customer and time.
Information concerning the needs of customer, sales of product, quality, and cost profit among
others is provided. This is facilitated where there are aggregates with complex conditions.
Lastly, we have its benefit in analysis of effectiveness of sales campaigns.
Significance of its implications in terms of business benefits and/or improving quality of
life;
The first significance is in the analysis of effectiveness sales campaigns which is done so as to
promote products and attracts customers.
Secondly, we have multidimensional analysis of sales, product, customer and time which
facilitates analysis on aggregates with complex solution.
On the other hand, designing and constructing data warehouses is also its usefulness. The
design and development of data warehouse structures depends on data mining knowledge.
Customer retention can’t go unmentioned. This is done with the aim of making suggestions of
adjustments necessary to capture the customer loyalty (Günnemann, Kremer, & Seidl,
2011).