As they say, data mining is the art of extracting important information from large amounts of unstructured data. For example, if you have a family tree and need to know the generation, then it would be much easier if you could extract that information with the help of a data mining technique.
Data mining is a type of data extraction that is done on all kinds of documents such as the text in email or the documents from the internet. The information that you will extract is called attributes, and each attribute can be classified in various ways.
The first part of data mining is the classification of the data that needs to be extracted. You should classify the data using three different classifications: first is the frequency, second is the categorical, and third is the dimensional.
How to Extract Data With the Help of Data Mining Spreadsheets
The first classification is quite similar to the English classification system. A frequency classification is the one that categorizes the data on the number of occurrences. On the other hand, a categorical classification is one that identifies the subject of the data.
The second classification of data mining is called the classification by meaning. This classification deals with the means that are used for extracting the data. In the case of the Internet, the information usually comes from tags, hyperlinks, or keywords.
Then, the final classification deals with the value of the data that is extracted. Some of the classes are the numeric, the real, the dimension, and the relative. The numeric classification is based on integers and the real classification is based on strings.
The last classification deals with the units that are applied when extracting the data. In the case of the Internet, there are several types of units, such as bytes, characters, and pixels. The first classification of data mining is the label class, which is the one that is used to identify the units.
The name of the units also plays an important role in the classification of the data. The classes such as size, mass, time, and duration are commonly used. As a result, the dataset that is processed can be easily identified.
There are some additional considerations that you should take into account. The first one is that you must be careful that the data will not contain any other important data that may make the classifications hard.
For example, when there is a lot of data in the database that is collected from different places and is then connected, the classifications can be quite hard to recognize. Therefore, there is need for a classifier that is able to discriminate between the data that is related to each other. It is a process known as regression analysis, and you can use it to determine the relationships between the variables in the database.
It is also very important that you are able to process the data without the information being changed. In the case of databases, you should be able to get the correct classification.
Furthermore, it is also necessary to realize that the classification that you are using is not always the most appropriate one. To learn more about how the classification system works, you can always take advantage of the classes offered by the companies and the industry that you are in. PLEASE READ : data extraction from excel spreadsheet
