Searching the Web Using Text Mining and Data Mining

Searching the Web Using Text Mining and Data Mining

There are many types of financial analysis tools that are useful for various purposes. Most of these are easily available online. Two such tools of software for financial analysis include the text mining and data mining. Both methods have been discussed in details in the following section.

The features of Text Mining It is a way by which information of high-quality can be derived from a text. It involves giving structure to the input text then deriving patterns within the data that has been structured. Finally, the process of evaluating and interpreting the output is undertaken.

This form of mining usually involves the process of structuring the text input, and deriving patterns within the structured data, and finally evaluating and interpreting the data. It differs from the way we are familiar with in searching the web. The goal of this method is to find unknown information. It can be done with analyses in topics that that were not researched before.

What is Data Mining? It is the process of the extraction of patterns from the data. Nowadays, it has become very vital to transform this data into information. It is particularly used in marketing practices as well as fraud detection and surveillance. We can extract hidden information from huge databases of information. It can be used to predict future trends as well as to aid the company business to make knowledgeable quick decisions.

Working of data mining: Modeling technique is used to perform the operation of such form of mining. For these techniques, you must need to be fully integrated with a data warehouse as well as financial analysis tools. Some of the areas where this method is used are:

 - Pharmaceutical companies which need to analyze its sales force and to achieve their targets.
 - Credit card companies and transportation companies with sales force.
 - Also large consumer goods companies use such mining techniques.
 - With this method, a retailer may utilize POS or point-of-sale data of customer purchases in order to develop  strategies for sale promotion.

The major elements of Data mining:

1. Extracting, transforming, and sending load transaction data on the data warehouse of the server system.

2. Storing and managing the data in for database systems that are multidimensional in nature.

3. Presenting data to the IT professionals and business analysts for processing.

4. Presenting the data to the application software for analyses.

5. Presentation of the data in dynamic ways like graph or table.

The main point of difference between the two types of mining is that text mining checks the patterns from natural text instead of databases where the data is structured.

Data mining software supports the entire process of such mining and discovery of knowledge. These are available on the internet. Data mining software serves as one of the best financial analysis tools. You can avail of data mining software suites and their reviews freely over the internet and easily compare between them.

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Using Charts For Effective Data Mining

Using Charts For Effective Data Mining

The modern world is one where data is gathered voraciously. Modern computers with all their advanced hardware and software are bringing all of this data to our fingertips. In fact one survey says that the amount of data gathered is doubled every year. That is quite some data to understand and analyze. And this means a lot of time, effort and money. That is where advancements in the field of Data Mining have proven to be so useful.

Data mining is basically a process of identifying underlying patters and relationships among sets of data that are not apparent at first glance. It is a method by which large and unorganized amounts of data are analyzed to find underlying connections which might give the analyzer useful insight into the data being analyzed.

It's uses are varied. In marketing it can be used to reach a product to a particular customer. For example, suppose a supermarket while mining through their records notices customers preferring to buy a particular brand of a particular product. The supermarket can then promote that product even further by giving discounts, promotional offers etc. related to that product. A medical researcher analyzing D.N.A strands can and will have to use data mining to find relationships existing among the strands. Apart from bio-informatics, data mining has found applications in several other fields like genetics, pure medicine, engineering, even education.

The Internet is also a domain where mining is used extensively. The world wide web is a minefield of information. This information needs to be sorted, grouped and analyzed. Data Mining is used extensively here. For example one of the most important aspects of the net is search. Everyday several million people search for information over the world wide web. If each search query is to be stored then extensively large amounts of data will be generated. Mining can then be used to analyze all of this data and help return better and more direct search results which lead to better usability of the Internet.

Data mining requires advanced techniques to implement. Statistical models, mathematical algorithms or the more modern machine learning methods may be used to sift through tons and tons of data in order to make sense of it all.

Foremost among these is the method of charting. Here data is plotted in the form of charts and graphs. Data visualization, as it is often referred to is a tried and tested technique of data mining. If visually depicted, data easily reveals relationships that would otherwise be hidden. Bar charts, pie charts, line charts, scatter plots, bubble charts etc. provide simple, easy techniques for data mining.

Thus a clear simple truth emerges. In today's world of heavy load data, mining it is necessary. And charts and graphs are one of the surest methods of doing this. And if current trends are anything to go by the importance of data mining cannot be undermined in any way in the near future.

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