Weighing the Benefits and Limitations of Data Mining

The idea of Data Mining is growing in popularity in business activities. We are living in a data-driven age and we have been producing more and more data in every area that you might think about. Each time you make a sale, there’s data being transferring into a database, and there’s some sort of data download in most transactions you perform. With the increasing amount of available data, it is necessary to make use of this huge resource.

Data Mining is the practice of collecting real, new, comprehensible, and meaningful information from large databases and making important business decisions with it. Data Mining applies across all industries and fields. Generally speaking, wherever there are processes and wherever there is data, the application of the powerful mathematical techniques that make data mining possible remains applicable to make data usable for the processes which show that data is the solution to all problems.

But there always is a downside to the story. Data mining, no matter how useful it is, poses some real issues in its application. In this article, we will compare the pros and cons of this field and see how the Benefits outweigh the Limitations which ultimately makes the field successful.

Benefits of Data Mining


Moreover, data mining tools have proven to be beneficial in determining patterns in complex manufacturing processes. It is using in system-level designing to building the relationships between product portfolio, its architecture, and the data needs of the customers. Furthermore, it could enjoy forecasting the product development period and cost among the other tasks. Yet, there are a few key components that need consideration before mulling over how to mine data for manufacturing i.e. determining the ‘right data’.


Modern researchers in different fields experience an unprecedented complexity of data. Yet, the results provided to the researchers via traditional data analysis techniques offer limited solutions to such difficult conditions.

Finance/ Banking

The digitalization of the banking system is there to generate a huge amount of data with each new transaction. The data mining technique can help bankers by solving business-related concerns in banking and finance — identifying trends, casualties, and relationships in business information and market-cost that aren’t visible to executives or managers due to large data volume or are discoverable on the screen by experts. The manager may find these data for better focusing, obtaining, retaining, segmenting, and sustain a loyal and lucrative customer.


All businesses use data mining for marketing as it helps to forecast potential risks, boosts sales, reduces costs, and enhances consumer satisfaction. Also, it helps in competition analysis, market segmentation, and audience targeting or customer acquisition.


Data Mining can also be in use to design a better curriculum according to specific needs, as well as encouraging learning science. Moreover, an organization can use data mining to make accurate decisions and forecast the results of the student. Thus, applying data mining in the education industry will have long-lasting effects on the growth of our world.

Limitations of Data Mining


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