What can we do with mined data nowadays?

Aashim Bajracharya

Software Design Analyst

Data is anything that we see, perceive, hear, feel within the certain surrounding. Frankly speaking, data is everything. In this mother nature, various data are existing around us in simpler and complex structure.

Beside that, various data are extracted out from various data mining process such as, statistics process, clustering, visualization, decision tree making, making association rules, neural networking and classification process.

These mined data are sure to have essential uses in the field of the mankind and it should be too. By data mining, we can have certain applications and use of the data and they are stated right below.

Health Care prediction and Safety

 There is the best saying that, prevention is better than cure. It obviously is true, and this is well justified by the utilization of the mined data from the individual through various gears such as heartbeat, blood pressure, calories calculation which helps in the prediction of the health status of the each individual and by that data, on-time action can be taken to mitigate the health risk.

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Market Basket Analysis

 This analysis technique is the theoretical convention where it states that, if any person buys certain categories of the items, then by the data mining, retailer knows the behavior of the each customer and provides the stores layout according for the certain group of the customer. Using differential analysis, comparison of results between different stores and customers in different demographic groups can be done.

Educational Field

 Now a days, there is new emerging field in data mining, which is known as Educational Data Mining. This field is related to the data origination and mining from educational environments. The educational data mining predicts the students future learning behavior, effects of educational support and knowledge about learning. By the data mining, effective decisions can be taken to predict the result of the student.

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Customer Relationship Management

 This management is all about acquiring the customers as many as possible and retaining them with improved loyalty with them. In this management, there is the crucial role of the data mining process. For the proper relationship with customer, data is needed to be collected and information is analyzed from the collected data.

Detecting Fraud and Intrusion

 Due to the nuisance action of the various types of the frauds, huge amount of money have been lost. Its very tedious and time licking to detect fraud by traditional methods of the fraud detection. By the essential process of data mining, this helps in acquiring the helpful and meaningful patterns of the frauds and taking valuable information from this patterns and detect the fraud effectively. By using the collected data, algorithm is created to identify if the certain record is fraud or not.

Similarly, in case of intrusion detection, it is about preventing the compromising of the integrity and confidentiality of a resource from the unauthorized access. In this case, by data mining can take ultimate role by adding a level of focus to anomaly detection. Therefore it ultimately helps to extract data which is more relevant to the problem.

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Lie Detection

Its general that apprehending a criminal is easy whereas bringing out the truth from him is difficult. Law enforcement can use mining techniques to investigate crimes, monitor communication of suspected terrorists. This registered file includes text mining also. This process seeks to find meaningful patterns in data which is usually unstructured text. The data sample collected from previous investigations are compared and a model for lie detection is created. With this model processes can be created according to the necessity.

Customer Segmentation and Financial Banking

Traditional market research may help us to segment customers but data mining goes in deep and increases market effectiveness. Data mining aids in aligning the customers into a distinct segment and can tailor the needs according to the customers. Market is always about retaining the customers.

Data mining allows to find a segment of customers based on vulnerability and the business could offer them with special offers and enhance satisfaction.

With computerized banking everywhere huge amount of data is supposed to be generated with new transactions. Data mining can contribute to solving business problems in banking and finance by finding patterns, casualties, and correlations in business information and market prices that are not immediately apparent to managers because the volume data is too large or is generated too quickly to screen by experts. The managers may find these information for better segmenting,targeting, acquiring, retaining and maintaining a profitable customer.

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Corporate Surveillance

Corporate surveillance is the monitoring of a person or group’s behavior by a corporation. The data collected is most often used for marketing purposes or sold to other corporations, but is also regularly shared with government agencies. It can be used by the business to tailor their products desirable by their customers. The data can be used for direct marketing purposes, such as the targeted advertisements on Google and Yahoo, where ads are targeted to the user of the search engine by analyzing their search history and emails.


Since Bio Informative is rich in data, Data Mining approaches seem ideally suited for Bioinformatics. Mining biological data helps to extract useful knowledge from massive data sets gathered in biology, and in other related life sciences areas such as medicine and neuroscience. Applications of data mining to bioinformatics include gene finding, protein function inference, disease diagnosis, disease prognosis, disease treatment optimization, protein and gene interaction network reconstruction, data cleansing, and protein sub-cellular location prediction.

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