Are you looking for what data mining and its applications are? AAmcourse is here to help with your search. In this article, we will discuss what data mining is, its process, and the applications of data mining.
Every business has a lot of data they need to collect, analyze and use. The data differ in nature and represent unique factors of the business. The question arises is what type of data is to be used and how to find it in the data pool; that’s where data mining comes in.
We live in a world full of readily available data. The problem is the volume of data. Due to the large volume of data, it becomes more challenging to find the specific data you are looking for. Data mining helps us to find that data.
Before we move on to the applications of data mining, let’s take a look at the basics. Without further ado, let’s study what data mining is.
Data Mining
Data mining is analyzing raw data to search for relationships and find hidden patterns, anomalies, and correlations to create usable information. But that’s not all; data mining is also used to forecast future events. Data mining is also known as Knowledge Discovery in Databases, Knowledge extraction, data and pattern analysis, information harvesting, etc.
Businesses use data mining to analyze their business and its aspects. Data mining helps firms collect reliable and useful information for each department, such as sales, costs, etc. Businesses use data mining to predict future trends, which helps to make more effective decisions.
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The Data Mining Process
Recognize the Nature of Business
The first and foremost step of the data mining process is understanding the nature of business. In this process, the analyst has to study the objective of the business. The analyst must learn about the business, their end goal, and why they are using data mining.
Simply, the analyst has to analyze the current poison of the business, their vision, and what is success for them.
Understand the Nature of Data
Once you have analyzed the business and its nature, time to move to the required data. The analyst must recognize what data type is needed for the process. Once the data type is established, the analyst must research data sources, how to procure that data, and how to represent and use the data.
Prepare the Data
After the data have been procured and stored, the next step is to mine out useful information from the data. The outliers, rogue, incomplete, and inconsistent data are cleared out to clean the data. Once cleaned and filtered, the information is checked for mistakes.
Preparing a Predictive Analytical Model
The analyst uses different data mining techniques to establish relations and find hidden patterns and trends in the information. These data are used as input for predictive models that use the data as the base to provide future outcomes. It helps businesses to make more accurate and practical decisions.
Evaluate the Results
The analyst takes the various outcomes of the model and presents them to the decision-makers. Then it’s on the decision-makers to select the best alternative and make their decisions. The management selects the least expense or the most profit, whichever is more beneficial.
Implement the Changes and Monitoring
The last phase in the data mining process is to implement the changes according to the decision taken by the top management. Even after implementing the change, the management monitors the progress and evaluates if the new strategy is working as planned or not.
Let’s move on to the main part – The applications of data mining.
Applications of Data Mining
Banking Industry
The first in the list of applications of data mining is in banks.
Data mining helps banks with their credit and anti-fraud systems. It analyzes customer credit, customer transaction data, and card transactions. It also allows banks to understand their customers’ online preferences, which can be helpful for their marketing campaigns.
Healthcare Industry
The second in the list of applications of data mining is in the Healthcare industry.
Data mining helps to gather all the data regarding a patient’s history, examination results, medications, and treatment patterns. The data helps the doctors create a more accurate diagnosis, which will ensure the patient receives proper treatment.
Marketing Department
The next in the list of applications of data mining is in the marketing field.
Marketing is one of the fields that use data mining the most often. The marketing department has to study the customer, their needs and wants, market trends, etc. The marketing team must ensure they know their target audience and the market.
Data mining helps the marketing department collect data about their customer base, such as age, gender, income level, preferences, location, etc. This data is used for decision-making and marketing campaigns. It helps the business to retain its existing customer and gain new ones.
Retail Industry
Next on the list of applications of data mining is in Retail shops.
The retail and marketing worlds go together but are still quite different. Retail shops and supermarkets use data mining to analyze the purchase made by customers for restocking. The more selling product is restocked again as people buy them. Data mining also helps them to understand which marketing advertisements are most effective for customers.
Research
The 5th on the list of applications of data mining is in research.
Researchers use data mining to search data from the pool of information available. Data mining provides tools for clustering data according to their attributes, performing predictions, selecting data, etc., which are useful in research for looking for and sorting data.
Education
The next on the list of applications of data mining is in the educational field.
In today’s generation, where more and more people are moving towards education, it becomes a perfect opportunity for everyone to analyze people’s needs and provide them with what they want. Educational hubs use data mining to examine what courses have created an interest in people’s minds by analyzing the data about the enrolment of people in specific fields.
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Advantages of Data Mining
- It helps businesses to gather accurate and reliable information quickly.
- Data mining helps businesses with decision-making.
- It helps businesses to make effective operational decisions.
- Data mining helps business to understand their customer base and its preferences.
- Data mining uses both the new and the legacy systems.
- It helps the banking industry in analyzing their customer’s credit.
Drawbacks of Data Mining
- Data mining tools are complex and hard to use. Hence, the analyst must be well-equipped to work with data mining tools.
- There are various tools for various purposes. If the analyst doesn’t understand them, the outcome will be faulted.
- Data mining tools are only useful if the data is correct. Incorrect data will ultimately lead to wrong predictions.
- Advanced technologies also lead to crimes, and data mining can cause such problems if used that way. The customer data collected can be sold to other businesses, invading people’s privacy.
- Data mining can only be used on large amounts of data to reflect patterns and trends.
- Data mining is a costly tool because of the variations and tools it offers.
Along with the Applications of Data Mining, ALSO READ ABOUT: 13 Important Types of Data Visualization Tools That are used in Business
FAQs
Where are the applications of data mining used?
There are 6 major industries where the applications of data mining are used. They are as follows:
Banking Industry
Healthcare Industry
Marketing
Retail Industry
Research
Education
How does Netflix use data mining?
Netflix uses data mining to collect individual reports about watch history, location, ratings, and preferences and make predictions and suggestions to the individual based on the results.
What are the five major types of data mining tools?
Sisense
Rapid miner
Orange
Monkey learn
Weka
What are the 5 main data mining techniques?
Data warehousing, data visualization, machine learning, neural networks, and prediction models are the 5 main data mining techniques.
Closing Statement
Data mining is a research tool that helps businesses to analyze their current and past performance. It studies the data and finds hidden patterns and relations in the data. Based on the information, it enables the management to make decisions that best suit the business’s future. Data mining is used in several fields, such as marketing, banking, education, and more. Many field where the applications of data mining are used are mentioned in the article. It offers various tools suitable for all types of data.
I hope this article about the applications of data mining is informative. If you have any doubts or suggestions, write them in the comment box.