Do you want to know about Data Mining Definition?. If yes, then give your few minutes to this article, in order to get full knowledge in Data Mining. And make yourself ready to dive into Data Mining Field.
Hello, & Welcome!
In this blog, I am gonna tell you-
- Why Data Mining?
- Data Mining Definition?
- Data Mining Process.
- What kind of Data you can mine?
- Technologies Used in Data Mining.
- Application of Data Mining.
Firstly, I would like to start with-
Why Data Mining?
There is a popular saying that “We are living in an information age” but according to the facts, ” We are living in the data age”. Yes 🙂 I am right. The huge amount of data is generated daily by various sources. These sources are computer networks, search engines, social media, medical departments, science, business, and many more.
In business, such as amazon site generates a huge amount of data daily. They handle millions of transactions daily, plus different customer details, their shopping trends, and many more.
Similarly, in the medical department, lots of data is generated on a daily basis. For example, patient records, medical records and many more. In the search engine, tons of data generates daily due to a huge number of searches.
In Social Media, the user generates a vast amount of data daily either by uploading an image or by sharing the posts.
That’s why we are living in the data age, no doubt. And this huge amount of data contains very useful information. So, in order to find out useful information from these tons of data, the Data Mining comes into the light.
Data Mining finds out the relevant information from the huge amount of data. That’s why it is very important in the data field.
Data Mining Definition–
You can say Data Mining to “Knowledge Mining from the Data”. In short, Data Mining is “Knowledge Mining”. Because of Data Mining find out the relevant information or knowledge from the data tank.
Data Mining performs the same job as in “Gold Mining”. In “Gold Mining”, gold is mined from the rock or sand. Similarly, in “Data Mining”, data is mined from a huge amount of waste data. Data Mining mines only useful data.
There are various synonyms of Data Mining as “Knowledge Mining”, “Pattern Mining”, “Knowledge Extraction”, etc. You can also call Data Mining to “Knowledge discovery”.
Data Mining Process-
Process of Data Mining contains following steps-
- Cleaning of Data.
- Data Integration.
- Reduction of Data.
- Transformation of Data.
- Data Mining.
- Pattern Evaluation.
- Presentation of Knowledge.
1. Cleaning of Data-
The data which we collect is incomplete and noisy. So, to clean the data, the very first step in data mining is data cleaning. In the data cleaning process, we clear missing value and noise.
Missing value means many fields are blank in data. So we fill the blank in the cleaning process of data.
2. Data Integration-
In Data integration, we combine data from multiple sources. Because data is not collected from a single source. We collect data from multiple sources and then we combine it into one. So, in data integration, you must be careful that no redundant or inconsistent data may come.
In data integration, you need to perform correlation analysis and entity identification.
3. Reduction of Data-
The data which we collect is huge in size. So to perform data mining on huge data size is very time-consuming. That’s why we perform data reduction to reduce the size of data.
Wavelet Transform and Principal component analysis are very popular methods for data reduction.
4. Transformation of Data-
In data transformation, we transform the data in a suitable format to perform data mining. Different strategies are used for data transformation including smoothing, aggregation, normalization, etc.
5. Data Mining-
After data transformation, data mining is performed. Various interesting patterns are found in the data mining process.
6. Pattern Evaluation-
Data Mining finds lots of patterns, but all patterns are not interesting. So, in this step, the interestingness of patterns is found. The pattern who is more interesting is kept and the rest of the patterns are removed. This interestingness is observed by some “interestingness measures”.
7. Presentation of Knowledge-
Once the patterns or knowledge is mine, we represent this knowledge to the user. This is the last and final step in the data mining process.
What kind of Data you can mine?
You can perform data mining on any kind of data, but the basic form of data included-
- Database Data
- Data warehouses.
- Transactional Data.
- Multimedia Data.
- Spatial Data.
- Web Data.
Technologies Used in Data Mining.
In Data Mining, various technologies are used. Here I am gonna tell you some of the technologies, which data mining use.
- Machine Learning
- Pattern Recognition.
- Data warehouse.
- Information Retrieval.
Application of Data Mining-
Data Mining performs great in almost every field. Here I am gonna tell you some application areas of Data Mining, where data mining plays a vital role.
Data Mining is the core of the business industry. Without Data Mining, I believe the business industry is not complete nowadays. Different business industries are using data mining according to their needs.
For example, in Amazon, lots of users purchase items daily. So amazon collects these user’s data, performs mining and finds out various patterns in shopping. Like if you go on Amazon and purchase a laptop and Headphone. So when you visit next time on Amazon, you will see another laptop and headphones in the Recommendation. This is nothing but a Data Mining.
Another example of Data mining in business is of a supermarket. So after performing mining on supermarket data, it is found that when someone purchases bread, he or she also purchases a Jam. So by using this pattern, the supermarket manager can increase the sale of Jam by putting bread and Jam together.
In Search Engine-
Search Engine is a very large application of Data Mining. When you search something on search engines like google, so search engine stores your data
On the basis of your search history, the search engine gives you recommendations. Like if you search related to camera type and prices. So you will get recommendations related to the camera.
I hope now you understand Data Mining Definition, its process, and the importance of why it is so much popular nowadays.
All the Best!
Though of the Day…
‘ It’s what you learn after you know it all that counts.’– John Wooden