What Is Data Mining?

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What Is Data Mining?

Posted On : Nov-15-2012 | seen (690) times | Article Word Count : 556 |

Often referred to as knowledge discovery, data mining is the analyzing of data from different perspectives. After analysis, it needs to be translated into information that is used to do things such as increase a company's revenue and cut operation costs. There are many tools used in the process of mining data, including mining software. It may sound complicated, but after reading a brief introduction to data mining, it will be easier to understand what data mining is all about.

Data Mining Means Continuous Innovation

Although data mining is a new phrase in technology, the actual technology is not new. Market research firms have been using computers to sift through data for years, allowing them to determine how consumers are spending. Innovation in processing power and disk storage has been happening for years and allows for increased accuracy and lower prices.

Data, Information, Knowledge and Data Warehouses

There are three important aspects of data mining. They are data, information and knowledge. Data includes the facts, numbers and text that is processed by computers. There are different formats of data in data mining. They include transactional data such as sales and inventory, non-operational data such as industry sales, and meta data such as logical database design. Information refers to the patterns, associations and relationships among the data. The knowledge is what is processed from the information and includes historical patterns and future trends. Data warehouses are a reference to the process of data management. It represents the ideal vision of keeping all data organized and is needed to maximize success. Each of these aspects of data mining are very important and are taught in business intelligence training.

What Data Mining Does

Data mining is most often used by companies that focus on consumers. It allows them to determine the correlations between internal factors and external factors. Internal factors refer to things such as the price and product positioning while external factors include economic indicators and customer demographics. These relationships determine the type of impact on sales and profits of a company. Simply put, data mining turns data into information.

How Data Mining Works

Data mining analyzes relationships and patterns based on a user's queries. A variety of data mining software is available, including machine learning and neural networks. Four kinds of relationships are present in data mining. They are classes, clusters, association and sequential patterns. Classes refers to stored data that searched for other data in pre-determined groups. Clusters are groups of information based on their relationship to one another. Clusters must be logical. Association identifies the associations between data whilesequential patterns are mined to show future behavior patterns and trends.

The Five Elements of Data Mining

There are five major elements that are involved in data mining. First, the data is extracted to the data warehouse system. Next, the data must be managed in a multidimensional system. After that,the data isprovided to business analysts. The business analysts then analyze the data with the application software and present the data in a format that is useful to the companies.

Data mining sounds complicated and scary, but it is an up-and-coming field that is now standard in business intelligence training. Hopefully the brief introduction to data mining was helpful in teaching the basics of the operation.

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<h1>What Is Data Mining?</h1> Author: <a href='http://www.articleseen.com/profile_Mr William Hauselberg.aspx'>Mr William Hauselberg</a> Often referred to as knowledge discovery, data mining is the analyzing of data from different perspectives. After analysis, it needs to be translated into information that is used to do things such as increase a company's revenue and cut operation costs. There are many tools used in the process of mining data, including mining software. It may sound complicated, but after reading a brief introduction to data mining, it will be easier to understand what data mining is all about.

Data Mining Means Continuous Innovation

Although data mining is a new phrase in technology, the actual technology is not new. Market research firms have been using computers to sift through data for years, allowing them to determine how consumers are spending. Innovation in processing power and disk storage has been happening for years and allows for increased accuracy and lower prices.

Data, Information, Knowledge and Data Warehouses

There are three important aspects of data mining. They are data, information and knowledge. Data includes the facts, numbers and text that is processed by computers. There are different formats of data in data mining. They include transactional data such as sales and inventory, non-operational data such as industry sales, and meta data such as logical database design. Information refers to the patterns, associations and relationships among the data. The knowledge is what is processed from the information and includes historical patterns and future trends. Data warehouses are a reference to the process of data management. It represents the ideal vision of keeping all data organized and is needed to maximize success. Each of these aspects of data mining are very important and are taught in business intelligence training.

What Data Mining Does

Data mining is most often used by companies that focus on consumers. It allows them to determine the correlations between internal factors and external factors. Internal factors refer to things such as the price and product positioning while external factors include economic indicators and customer demographics. These relationships determine the type of impact on sales and profits of a company. Simply put, data mining turns data into information.

How Data Mining Works

Data mining analyzes relationships and patterns based on a user's queries. A variety of data mining software is available, including machine learning and neural networks. Four kinds of relationships are present in data mining. They are classes, clusters, association and sequential patterns. Classes refers to stored data that searched for other data in pre-determined groups. Clusters are groups of information based on their relationship to one another. Clusters must be logical. Association identifies the associations between data whilesequential patterns are mined to show future behavior patterns and trends.

The Five Elements of Data Mining

There are five major elements that are involved in data mining. First, the data is extracted to the data warehouse system. Next, the data must be managed in a multidimensional system. After that,the data isprovided to business analysts. The business analysts then analyze the data with the application software and present the data in a format that is useful to the companies.

Data mining sounds complicated and scary, but it is an up-and-coming field that is now standard in business intelligence training. Hopefully the brief introduction to data mining was helpful in teaching the basics of the operation.
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