Overview of Data Mining Applications
Data mining is the way in which the patterns in large data sets are viewed and discovered by making use of intersecting techniques such as statistics, machine learning and the ones like database systems. It involves the extraction of data from a set of raw and unidentified set of data in order to provide some meaningful results by means of mining.
The extracted data then is further put to use by making use of transformation and ensuring that it is being put to best use as per business requirements and needs. In this article, we are going to read about the various applications associated with data mining.
List of Data Mining Applications
Here is the list of various Data Mining Applications which are given below –
1. Financial firms, banks, and their analysis:
There are a large number of data mining techniques that are involved in critical banking and financial data providing and keeping firms whose data is of utmost importance. One such technique is distributed data mining which is researched, modeled, crafted and developed to help in tracking suspicious activities or any kind of mischievous or fraudulent transactions, be it related to the credit card or net banking or any other banking service.
By sampling and identifying a huge set of customer data, analysis becomes quite an easy task and tracking suspicious activities becomes a comparatively easier task by keeping a tab of the parameters such as the period of transactions, geographical locations, mode of payments, customer activity history, etc. Based on these parameters the customer’s relative measure is then calculated which can be put to any form of usage based on the indices calculated.
The bank can retain their customers or work in acquiring a new set of customers by performing a right set of data mining on the historical data and the nature of their activities. The data plays a huge role in the success and failure of any organization, especially after the advent of big data. The alluring offers can then be launched based on the customer’s activity and historic trends of transacting and purchase. The correlation among various financial indicators can be found out by making use of data mining. The patterns and the rise and fall of the stock markets and their predictions can also be analyzed by making use of data mining.
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2. Health care domain and insurance domain:
The data mining related applications can be used to efficiently track and monitor a patient’s health condition and also can help in efficient diagnosis based on the past sickness record. In a similar manner, the growth of the insurance industry depends on the ability to convert the data into knowledge form or by providing various details about the customers, markets and the prospective competitors and therefore all those companies who have applied the data mining techniques efficiently have reaped the benefits. This is applied over the claims and their analysis i.e. identification of the medical procedures which are claimed together. It enables the forecasting of new policies, helps in the detection of risky customer behavior patterns and also helps in the detection of fraudulent behavior.
3. Application in the domain of transportation:
The historic or the batch form of data will help in identifying the mode of transport a particular customer generally opts for going to a particular place, say his home town and thereby providing him alluring offers and heavy discounts on new products and launched services. This will thus be included in the genre of targeted and organic advertisements where the prospective leader of the customer generates the right to converted the lead. It is also helpful in determining the distribution of the schedules among various warehouses and also among outlets for analyzing load based patterns.
4. Applications of data mining in the field of medicine:
In the case of medical analysis, a patient’s case can be analyzed by making a tab of his clinic visits and the season of his visits. It also helps in the identification of patterns that have successful medical therapies for various kinds of illnesses. Researchers are making use of multi-dimensional data to reduce costs and improve the quality of services being provided today with extensive and better care. Other approaches such as soft computing, statistics, data visualization, and machine learning are used efficiently to gauge and predict the data volume of patients within a single category. The processes are developed to ensure that the patients receive appropriate attention whenever needed. It also helps healthcare and medicine based insurers detect fake and fraud cases.
5. Education:
In the field of education, the application of data mining has been prevalent where the emerging field of educational data mining focuses mainly on the ways and methods by which the data can be extracted from age-old processes and systems of educational institutions. The goal often is provided by the fact of making a student grow and learn in various facets using advanced scientific knowledge and here data mining comes majorly into play by ensuring that the right quality of knowledge and decision making content is being provided to the education departments.
6. Manufacturing Engineering
The data can be assessed by ensuring that the manufacturing enterprise possesses the right set of knowledge as its asset lies in the identification of the right set of product portfolios, product architecture and also between the customer needs and requirements. Moreover, efficient data mining capabilities can ensure that product development is being completed in the relevant time frame and does not exceed the budget allotted initially.
Conclusion
We have studied a basic overview and a layout of the usage of various data mining applications in different domains. Not to mention the scope of this huge and endless technique is not confined with these sectors only but also extends to every domain a business can flourish in.
It is only about the right techniques and some analysis to make your usual normal business be a differentiator among the competitors. The world today is running behind data and its management and efficient handling is the key factor that impacts majorly the growth of an organization, especially in today’s times. Hope you liked our article. Keep collecting data, analyze them and keep reading our blogs for more technology-related articles.
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