CONCEPT OF DATA MINING

Ever wondered how emails get filtered into different categories like promotion, social and spam on its own? Well, that is just one of the numerous applications of Data Mining.

What is Data Mining? It is the process of making known patterns, finding anomalies and relationships in large datasets that can predict future trends. The major purpose of Data Mining is to extract valuable information from data or to discern certain behaviors.

We can also see Data Mining as the extraction of hidden predictive information from an extensive database. It is a powerful technology with great potential to help organizations focus on the most important information in their data warehouses.

Just as Gold is processed from its natural state to a refined and detailed piece, a large amount of data can also be processed and filtered to get a required piece of information. The ability of data to be processed from its original state to a detailed state in this context is made possible by Artificial Intelligence.

TYPES OF DATA MINING

There are various forms of data mining, some of which include:

1. Text Mining:Text mining is the process of converting unstructured text into a structured format to identify meaningful trends. It can include text from sources like customers' feedbacks or social media.
2. Pictorial Data Mining: It is the analysis of multidimensional relations through changing extracted data into artificial pictures. It is extremely useful in areas of safety, such as flight control, power plant monitoring, etc.
3. Social Media Mining: In social media data mining, information from social media platforms is made whole by pieces from different sources, and analyzed to identify patterns and trends or make certain decisions. The combined unstructured data, profiles, posts, images, can then be used to identify behavioral patterns. Social media APIs and web scraping can be used to mine information from social media.
4. Web Mining: Web mining is the application of data mining techniques to identify trends from the World Wide Web. As the name implies, it is the information gathered by mining the web.
5. Audio and Video Mining: Audio and video mining is a technique by which the content of an audio and video signal can be automatically analyzed and searched.

FEATURES OF A DATA MINING SYSTEM

1. Creation of actionable information.
2. Prediction of likely outcomes.
3. Automatic discovery of patterns.
4. Focus on large data sets and databases.
5. Large quantities of data are been processed.

APPLICATIONS OF DATA MINING

Data Mining can be used in:

1. Healthcare Industry
2. Education Field
3. Customer Segmentation
4. Decision-making from mined customers' feedbacks.
5. Financial Industries, to determine what causes price fluctuation.
6. Telecommunication Industry and so on...

HOW DOES DATA MINING WORK?

In general terms, Data mining is made possible by walking through the following steps:

STEP 1: Detection of irregularities and identification of unusual values in a dataset.

STEP 2: Discovering existing relationships within a dataset. This frequently involves regression analysis, a statistical method of identifying which values have an impact on a topic of interest.

STEP 3: Clustering: Identifying structures (clusters) in unstructured data.

STEP 4: Classification: Generalizing the known structure and applying it to the data.

POSITIVE IMPACTS OF DATA MINING?

1. Data Mining helps organizations to make knowledge-driven decisions.
2. It helps to analyze a reoccurring pattern and predict future trends.
3. It helps to point out keywords faster that can be applied in different areas in an organization or the development of an application.
4. Data mining helps to make the best use of sophisticated data.

BEST PROGRAMMING LANGUAGES FOR DATA MINERS

1. Python
2. R
3. SAS(Statistical Analysis System)
4. SQL

REFERENCES:

• https://corporatefinanceinstitute.com/resources/knowledge/other/data-mining/
• https://www.investopedia.com/terms/d/datamining.asp
• https://www.upgrad.com/blog/data-mining-techniques/

This article was written to get newbies a sharp and precise understanding of what Data Mining is all about.

I hope you found this piece insightful😊! You can reach out to me here. Bye👋