15 Most Useful Applications of Data Mining

15 Most Useful Applications of Data Mining

Data mining comes into the picture when large sets of data are looked into for assisting the processes involved in Database Systems, Machine Learning, as well as Statistics.

Data mining applications have not only helped in financial data analysis in various organizations but also has helped in sectors like retail and scientific sectors.

In research done by Statista, it has been found that various Chief Procurement officers across the world gave the following data

  • Around 57% of applications are used in intelligent and advanced analytics for negotiations
  • About 56% is used for the process of efficiency improvement
  • Roughly 44% is put in utilization for market intelligence
  • Approximately 40% is applied for optimization of supplier portfolio

There are many examples of data mining which come helpful in analyzing information. Some of these are listed below

1. Analysis of market basket

This particular tool comes handy for a retailer who would like to know his prospective clients for a new line of products through the demand of an existing set of products which have been prominent in the market.

Such a tool helps the particular retailer to understand the needs of the customer and accordingly earn revenue through their business. It is one of the data mining uses which come handy in retail.

The concept here is based upon the basket of products where the client includes the products in his or her list while being in the store for their necessities. Data mining does not only come handy for existing customers, but it also helps in catering to the needs of new clients as well.

2. Improving analysis in the healthcare sector

Healthcare sector requires more attention due to change in climatic conditions and lifestyle patterns. For this very reason, the services and medicines are required which come to the patient at a specified cost.

Data mining shall help in locating affordable healthcare for various people belonging to different financial tiers. With this, healthcare can be developed in various locations where people can afford the best for their cure irrespective of the location.

3. Educational Data Mining

The EDM or the Educational Data Mining mostly comes handy in the situations where career counseling is given to the students to choose their stream as many due to the scoring of low marks in semesters take a drop year and end up being depressed. Such data mining shall help the students in know their path as their scores can be predicted with the help of their past data. The statistics of their marks can help in deriving the stream or branch of studies they would like to take up for pursuing their career with the help of DM application.

4. Customer Relationship Management

CRM is mostly observed in banks and other financial institutions where tracking records of all their customers can be done without any hassles.

Tracking financial details of every client through their phone numbers, names, account numbers, or specific codes can only be done through CRM software.

Also, if the bank wants to offer some privileges like a credit card or other vouchers to their clients, it is the Customer Relationship Management that comes in handy for checking their eligibility for the same.

5. Use in the Engineering sector

Application of data mining is also applicable in the engineering sector where manufacturing is the prime process which needs to be monitored in such a way that the product and human resource are tracked right from the warehouse till the gate.

Also, the amount of raw material used and quality checks run on the particular product can be monitored through the same tool. The monitoring of such data turns important as irresponsibility towards the same can turn a particular organization into losses.

6. Categorization of customers

This is yet one more area where data mining is applied. Every customer has certain needs and that all of them may not buy each and every product from the supermarket shelves.

For this very reason the putting customers into tiers so that only those clients be targeted which shall buy a certain product. This also helps in enhancing the customer experience in a certain store.

7. Detection of various factors

Data mining examples in the real world also relate to detection of various factors for keeping the data as well as the assets safe and secure from any theft or malpractices.

  • Fraudulent activities

Detection of fraudulent activities is taken care of by data mining in a way that all back-dated data is available in the database even when the culprit thinks that no evidence has been left behind after the crime. Many insider trading activities have been traced due to data mining.

  • Alertness against intruders

Just like a dog barks when a stranger trespasses the premise, data mining also helps in protecting against all such intruders through tools like authenticating the user, curb down errors while programming, and protecting the information with appropriate coding in a way that the data cannot be stolen in any way.

  • Detecting Lies

Most of the people might think that how data mining might help in lie detection in crime bureaus when a machine is used for the same. The data which is fed into the machine comprises of the structure and patterns of the ways in which a particular suspect lying in the custody is speaking the truth or not.

8. Digital banking segment

As banking services have become highly digitized in a way that money is transferred in a click of a finger rather than the traditional two to three days.

Clients for banking may have increased through the years but the grievances due to payment issues have risen. This is mainly due to network or server issues which occur and the client fails to get the information regarding the same.

Data mining helps the bank assist their clients by giving them the appropriate data for problem-solving of their clients regarding payments.

9. Analysis of Research

Mining of data in research analysis is important as the volume of data is huge in the organization which is managed through a cloud server.

It is not possible for a certain analyst to manage such huge amounts of data alone without the use of a data miner and hence this tool is widely used for research firms enabling projects to get over on time without much hassle.

A data miner is installed for helping analysts to create secondary data available for other researchers in the domain.

10. Surveillance in the corporate

Monitoring the behavior of the employees through a data miner may sound weird but this can be possible by tracking the data access of the employee. Access to sensitive data of the organization leads to leaking it out to a fellow organization or a third party.

Hence, surveillance is set through data mining like a filter for data where there is a limitation on the data which can be shared or cannot be accessed at all by various employees for their use. Also, for accessing such data there is certain permission which is required.

11. Informatics pertaining to biology

Data mining out of a huge database in Bio informatics becomes necessary as there are multiple fingerprints which get stored in the system even after the people have resigned from the organization in such a way that the memory has not been formatted.

This has both the positive as well as the negative sides. Positive is that information of a past employee remains with the organization for its records.

The negative side reflects the storage space for fresh data in the system which is necessary to be fed for the ease of others.

12. Investigating criminal offense

Many crime web series have made it clear to the viewers that they too require a database for matching initials like fingerprints or past record to declare the suspect as a criminal in the eyes of the law.

The database is large as other sectors and also requires a data miner for getting only the required data for the particular investigation.

It shall become cumbersome for officers to close a case without such a tool as may take more time than usual and the criminal may be roaming freely on bail without valid evidence. Absence of a data miner may even complicate non-bailable offenses.

13. Assistance in sales

Just like other sectors, sales also require mining of data in such a way that only those people fit for the product shall be approached for marketing the product or the service.

Suppose the asset size of a salaried person shall be fit for a housing loan unlike a businessman having turnover over a million according to their taxation reports.

Such businessmen shall be given priority services like investments options for building a sound portfolio in the long run. This is essential for helping people to ensure closures and achieve their targets.

14. Supporting the Insurance sector

The claim settlement or grievance handling can sometimes turn out to be hectic for customer care executives in such a way that they would consume time in searching for data than solving the issues of their respective client.

Data mining comes handy in this case as data can be traced either through a code of the policy number or through the personal identification number.

The data can also be derived from the citizenship identification card as the information is already been stored in the database at the time of applying for the certain policy through ‘Know Your Customer’ norms of the insurance company.

15. Lending a hand in transportation

Road transportation companies may find it difficult to track their trailers and trucks even in the presence of a robust database. Mining of data according to the location to where the vehicle has been sent or to which organization it has been leased out to shall help in solving the data problems of a particular transporter.

Either small or large size of the database of the transportation business, tools like business statistics and database systems comes in handy for analyzing a certain set of data.

Data mining may also help in calculating the fact that which location or organization would raise a requirement of transportation in the future.

Conclusion

These are some of the trends in data mining that help various organizations in their operations for monitoring the databases in various aspects in such a way that the organizational structure operates seamlessly without any hassles of theft of the data.

Organizations prefer to mine data due to finding records or evidence of certain incidences and projects which may be highly confidential and important to the organizations in many aspects.

Data mining today is being installed and use in various sectors like finance and healthcare to improve the services and make a valid contribution to the economy.

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