7 Stages of Data Mining in the Process of Information Search

7 Stages of Data Mining in the Process of Information Search

Data mining is highly necessary when doing information search from a database within a device. Stages of data mining are consequential and can be lengthy, but the results are worth the wait. How is the process behind data mining to get the wanted information?

At the end of each work period, offices will hold meetings to evaluate that month’s overall performance. The data information within the office’s computers is essential for a smooth decision-making process.

The problem is, there are a lot of data acquired during that period, which in turn complicates the data search process. To solve it, data mining is tantamount to gathering the necessary type of information and data.

Understanding the Stages Data Mining

At a short glance, the term data mining is similar to mining activities. Both activities involve mining the goods before those goods are distilled to find the desired extract results. Both activities also rely on statistical and mathematical methods, when only now such methods are enhanced by the use of artificial intelligence to boost its work speed.

Data inside a computer is made from binary sets which lengths are on par with their sizes. The larger the data is, the longer the binary set’s length that a process must undergo. Data mining is a solution that can help us find the important information from the abundance of information within the database.

Also Read: What is Big Data and How Does Big Data Work?

Stages of data mining do not consist of a single concept, instead, they consist of several complicated concepts and techniques. This is why it is necessary to do data mining in seven stages, as the process requires data management during the process. The lengthy process is necessary for finding the desired information.

These are the stages that make up the whole process of data mining:

1. Data Cleaning

The first step in data mining is data cleaning. In this stage, all incomplete or error data will be deleted from the database. This cleaning process is important so that there are no error data that might disrupt the information search process.

2. Data Integration

Data integration is a process in which varied kinds of data are integrated for analysis. This data variation may include a database, data cube, or files. Data integration can also increase the data mining process’ accuracy and speed. This process also involves Additional Data Cleaning to delete several data that are similar to the previously deleted error data.

Also Read: The Definition and Differences between Data Base and Data Warehouse

3. Data Reduction

The third stage is used for gathering relevant data from the data integration stage. The resulting data is smaller, but the information content remains solid and accurate. There are several strategies in data reduction:

  • Dimensionality Reduction: Reducing the number of attributes within the data set.
  • Numerosity Reduction: Replacing the original data in a smaller data version to prevent lag when accessing.
  • Data Compressed: Compressing the original data to make it smaller in size.

4. Data Transformation

Next, the data will be transformed into a format suitable for the data mining process. Several data are gathered to make the next stage more efficient. In this regard, smoothing, aggregation, normalization, and discretization processes are parts of the data transformation process.

5. Data Mining

This is the main stage of the whole process. All of the data will be identified for their patterns and information. Potential patterns within the data will then be extracted to achieve the desired results. Classification and data cluster techniques are parts of data mining.

6. Pattern Evaluation

There are still two stages that need to be done after the data mining process, one of them being pattern evaluation. All interesting patterns within the data can be discovered in this stage. This method also relies on data summarization and data visualization to make the data easier to understand.

7. Knowledge Representation

Lastly, data is visualized to make it readable to the readers. The data visualization may take forms in data tables, reports, and other formats.

The lengthy data mining process involves several difficult concepts, which is why we must pay attention when doing it. Luckily, AdIns provides the PROFIND software that can help your data mining process. Your IT team no longer has to do the data mining process by themselves since this software can do all the stages mentioned above. Contact our team immediately to get the demo version of this software!

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Published date :

13 December 2021