Data mining is defined as extracting the information from the huge set of data and using it to make crucial business decisions. In other words we can say that mining is mining the knowledge from data that improves business efficiency.
Data mining brings a lot of benefits to businesses, society, governments as well as individual. However privacy, security and misuse of information are the big problems if they are not addressed and resolved properly.
Need of Data Mining
We need data mining mainly due to following reasons:
In field of information technology, we have huge amount of data available information from the huge set of data is called data mining. This information further can be used for various applications such as market analysis, fraud detection, customer retention, production control, science exploration etc.
Advantages of data mining
Data mining brings a lot of advantages when using in a specific industry. Some of the main advantages are:
1. Data mining predict future trends, customer purchase habits etc. Based on these trends, marketers can direct their marketing attentions to their customers with more accuracy.
2. Data mining helps marketing companies to build models based on historical data to predict who will respond to new marketing campaign such as direct mail, online marketing campaign etc. Through this prediction, marketers can have appropriate approach to sell profitable products to targeted customers with huge satisfaction.
Disadvantages of data mining:
There are few disadvantages of data mining, which are:
1. Because of privacy issues, people are afraid of their personal information is collected and used in an ethical way that potentially causing them a lot of trouble. Businesses collect information about their customers in many ways for understanding their purchasing behaviours trends. However businesses don’t last forever, some days they may be acquired by other or gone. At this time the personal information on probably is sold to other or leak.
2. Businesses on information about the employee and customers including social security number, birthday and payroll etc. There have been a lot of cases that hackers were accesses and stole big data of customers from big Corporation with so much personal and financial information available. So, security is a big issue in data mining.
Applications of data mining
Today, various industries organisations have been adopting data mining to gain competitive advantages and help business grow. Some of the common application area of data mining are:
Data mining in sales/marketing: data mining enables the businesses to understand the patterns hidden inside past purchase transactions, thus helping in plan and launch new marketing campaigns in prompt and cost-effective way. In sales and marketing, data mining is used for market basket analysis to provide insight information on what product combinations were purchased, when they were bought and in what consequence by customers. This information helps businesses to promote their most profitable products to maximize the profit.
Data mining in banking or Finance: data mining is used to identify customer loyalty by analysing the data of customers purchasing activities such as the date of frequency of forces in a period of time, total monetary value of all purchases and when the last purchase was. After analysing those dimensions, the relative measure is generated for each customer. To help Bank to retain credit card customers, data mining is used. By analysing the past data, data mining can help banks to predict customers that likely to change their credit card affiliation so they can plan and launch different special offers to retain those customers.
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