7 Advantages and Disadvantages of Data Mining | Limitations & Benefits of Data Mining

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4.09.2021

7 Advantages and Disadvantages of Data Mining | Limitations & Benefits of Data Mining


5 Advantages and Disadvantages of Data Mining | Limitations & Benefits of Data Mining
What is Data Mining ?

Data mining is a process where data is arranged systematically depending on the needs. In short it summarizes all the data and information for the sake of later use. It was introduced mainly to overcome the limitations faced during data analysis. 

Where is Data Mining used ?

Today, data mining is used in various fields such as business, healthcare, insurance, transportation and government. Especially, data mining is used by businesses to understand large amount of data so that they can come to better conclusion regarding business growth. 

Even though data mining offers countless advantages, it is still with some inconveniences. By knowing the pros and cons, the businesses can determine if its a worth investment.

In this article, I will be listing out the 7 Advantages and Disadvantages of Data Mining | Limitations & Benefits of Data Mining. Through this post, you will know the pros and cons of using data mining.

Let's get started,

Advantages of Data Mining


1. Business Management

Data mining process paves the way for new business opportunities. With all of the products, the right kind of business approach can be implemented using data mining. For an example, the right product can be delivered to the customer guarantying product sales. 

Other than that, with the data mining information the businesses will be able to approach with different marketing techniques.


2. Marketing Strategies

Using data mining techniques, the businesses can create data models. From this models, they could easily identify the customers who will be interested in their products. Thus, the products that the businesses will be bringing into the market can be guaranteed to be profitable. So whatever the products introduced will be contributing to profit growth of the company. 


3. Brand Strengthening

Whenever a company is launching a new product, the data mining techniques can be used to develop it better. With all the information gathered, it can be compared with the competitors so that companies will be able to understand their customers better. Hence, it is no doubt that data mining strengthens your company brand.


4. Data Analysis

For the purpose of data mining, various information are gathered on the basis of market. Even if there is large amount of data, the analyzing can be performed without any problem. And with the information collected from previous analysis, it is easy to maintain accuracy. 


5. Customer Identification

Each customer in the market is different in their own aspects. They are different in essence of behavior and characteristics. Hence, without a proper technique it is difficult to understand their preferences. Data mining helps businesses to recognize their customers effectively so that they are most likely to purchase their products.


6. Criminal Identification

With the information collected from market analysis, governments and other institutions can use them to identify criminals. For an example, the information can be arranged in a pattern that helps in analyzing past transactions of a customer. Hence, it could easily point out if there is any fraudulent activities.


7. Revenue Growth

Using data mining techniques, companies could arrange records of previously sold products. From these records, they could manufacture targeted products while cutting down unnecessary costs and services. Therefore, data mining eventually increases revenue.


Disadvantages of Data Mining


1. Cost

Data mining involves lots of technology in use for the data collection process. Every data generated needs its own storage space as well as maintenance. This can greatly increase the implementation cost. And also, for the tool selection and other operations, a specialist must be hired which can also contribute to the overall expenses.


2. Security

Identity theft is a big issue when using data mining. If adequate security is not provided, it could pose vulnerabilities in the security. Various information of the customers are collected in the data mining. With such huge amount of data, hackers could easily access them and steal critical information. 


3. Privacy

When using data mining there are many privacy concerns raised. The information that is collected for data mining can be used for purposes other than which it was created. Some could be leaked unknowingly or or else they would be sold to others intentionally violating user privacy. The ones who are able to acquire this data could potentially track individuals.


4. Accuracy

Even though data mining has paved the way for easy data collection with their own methods. Still it has limitations when it comes to accuracy. Information gathered can be inaccurate causing problems in decision making.


5. Technical Skills

There are different mining tools available based on their manners. Each of them might be with different algorithm and design. Without a proper technical knowledge the tool selection will be a difficult task. Therefore, a skilled technician needs to be deployed for the tool selection process.


6. Information Misuse

Apart from identity theft, the weak security present in data mining can often lead to misuse of information. People tend to use information from a data mining for their own personal gains. Or else a group of people can be targeted to be harmed from this information. Hence, it is the responsibility of the companies to ensure that the data is only used for the intended purpose.


7. Additional Information

Tremendous amount of information are collected by the data mining techniques. Not all the people feel convenient with this amount of data. Hence, it is necessary to maintain a limit of data collected through data mining techniques.

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