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#1 Posted : 30 August 2019 10:35:44(UTC)

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Introduction to Data Mining Techniques
In this Topic, we are going to Learn about the Data mining Techniques, As the advancement in the field of Information technology has to lead to a large number of databases in various areas. As a result, there is a need to store and manipulate important data which can be used later for decision making and improving the activities of the business.

What is Data Mining?
Data Mining is the process of extracting useful information and patterns from enormous data. Data Mining includes collection, extraction, analysis, and statistics of data. It is also known as the Knowledge discovery process, Knowledge Mining from Data or data/ pattern analysis. Data Mining is a logical process of finding useful information to find out useful data. Once the information and patterns are found it can be used to make decisions for developing the business. Data mining tools can give answers to your various questions related to your business which was too difficult to resolve. They also forecast the future trends which let the business people make proactive decisions.

Data mining involves three steps:
- Exploration – In this step, the data is cleared and converted into another form. The nature of data is also determined
- Pattern Identification – The next step is to choose the pattern which will make the best prediction
- Deployment – The identified patterns are used to get the desired outcome.

Benefits of Data Mining
- Automated prediction of trends and behaviors
- It can be implemented on new systems as well as existing platforms
- It can analyze huge database in minutes
- Automated discovery of hidden patterns
- There are a lot of models available to understand complex data easily
- It is of high speed which makes it easy for the users to analyze a huge amount of data in less time
- It yields improved predictions

List of 7 Important Data Mining Techniques
One of the most important tasks in Data Mining is to select the correct data mining technique. Data Mining technique has to be chosen based on the type of business and the type of problem your business faces. A generalized approach has to be used to improve the accuracy and cost-effectiveness of using data mining techniques. There are basically seven main Data Mining techniques which are discussed in this article. There are also a lot of other Data Mining techniques but these seven are considered more frequently used by business people.
- Statistics
- Clustering
- Visualization
- Decision Tree
- Association Rules
- Neural Networks
- Classification

From this article, we have known the important Data Mining techniques. And the characteristics and specifications of each of the technique are explained in detail. Data Mining is proved to be an important tool in many areas of business and the techniques are best used in deriving solution to a problem. Therefore it is very crucial for companies to use data mining techniques to help the business people to make smart decisions. No single technique can be used to solve the problem in business. All the data mining techniques should go hand in hand to solve out an issue.

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