what are the advantages and disadvantages of data mining?

Data mining is a tool that is largely used by organizations, companies, and governments as it collects and extracts data from a large sum of data. It uncovers the different data patterns so that the companies can get specific data for a product or any material to gain maximum benefit by reducing the factors that may devalue a certain product. The technique of data mining is being used by different firms frequently, as it saves a lot of time and produces results that are beneficial for the firms. Firms require additional methods to enhance and strengthen their marketing strategy, for which they advertise their work through marketing campaigns and for most interactions, the companies deliberate to write essays on the work they provide to promote their work and make their product reach more people by using strategies that are most reliable and can produce quick engagement with the product. Still, these methods should work effectively and should be cost-efficient. Cheap Law Essay Writing provides its assignment writing services to students in the UK and across the globe at reasonable pricing.

Advantages of Data Mining:

Following are some of the advantages defined by the experts at law coursework writing service that you get while using the data mining tool:

·         Retails: 

The product description is required to keep the market trends in the context, and Bigdata is extracted from a data mining tool, which makes it easy for the companies and organizations to keep track of the value and demand of the product in the context, and this is made easy by the data mining.  

·         Finance:

Datamining helps make transactions clear by collecting data from massive levels to fragmenting it into smaller units so that the customers can get full access to their transactions. It also maintains the credibility of the data provided and obtained from the users. Banks can create transparency and keep a record to secure them from fraud by giving loans to individuals.

·         Customer Groups:

Data mining helps increase the customer groups while collecting people's data and sorting it out, which will help them, target a specific audience with the product of their choice, strengthening their marketing strategies. In addition, firms can use different survey methods to help them identify the user that will increase customer interaction.

·         The loyalty of Brand:

The data mining technique is often used to create an atmosphere to buy the customers' loyalty. It will increase their interest in the products, and firms will record the customers' preferences to make their next interaction more useful and increase their loyalty to the brand.

·         Decision Making:

Businesses need to make such decisions that are beneficial for the productivity and growth of the company, which requires quick amendments that are beneficial. Data mining is used to generate ideas from the data collected by the mining technique. It makes it easy for companies to take effective decisions necessary for the firm's growth.    

·         Revenue:

Companies should take note of the products that are sold online so the company's revenue is generated in the excessive form, which will benefit the company. Still, with the mining technique, it is easy to collect the data from external sources, which makes it easy for the companies to keep an eye on the fluctuating rates of the market on the sale of productive.

·         Trends:

Data mining helps explore the new trends, and it also helps keep a static eye on the products that are more in demand and increase customer interaction with that product. It also looks for alternative products so that the company can work efficiently on these factors and can gain more profit via this technique. 

·         Optimization of Website:

With data mining, a company can easily look into the optimization of their website by using the mining tool, which improves customer interaction with the website, and it may involve data mining itself in the process.

Disadvantages of Data Mining:

Following are some disadvantages of the data mining technique:

·         Expensive:

The data mining technique is relatively expensive. It requires professionals and software to help the company or organization extract data from the provided sources, which most small-scale companies cannot use as they are not interacting with large companies. Hence, it is not a cost-efficient method and is not useful for most businesses. 

·         Experienced Person:

While using the data mining tool, it is prior that a skilful person is operating the tool that can work on the extraction of the information from the Bigdata and interpret the result of the outcome of the data mining. However, this is a challenging factor due to the lack of availability of the skilful persons.

·         Privacy:

Another aspect that cannot be looked out is that the privacy issues are most common in data mining, as this process involves a large amount of data from the different users and interprets it for their benefit, which breaches the privacy concerns of the individual, which also creates an atmosphere of unreliability over the big data. 

·         Security:

Similarly, while using data mining tools, security breaches commonly occur, which erodes the users' data. While extracting data from many users, the individual's data may be exploited by harmful sources and could be used against them. 

·         Inappropriate Information:

Since data mining extracts information from the Bigdata, the mining tool may collect irrelevant information from the users during the whole process, which is unnecessary for the company's demand and is time gaining to sort out minor details.

 

While interacting or using any technique or tool from a business point of view involves potential high-risk threats as there are always pros and cons attached to the secondary sources that a company use to improve their interaction with the customers and to keep a close eye on the preferences and current trends of the world. But, companies mustn't look down the consequences of such methods as they become the problems and may intervene in the growth of the business; therefore, potential persons should be hired who can keep cross-checks on these data drivers, and more benefit is earned by minimizing the cost limit.