Data Mining is the process of utilizing the results of data exploration to adjust or enhance business strategies. It builds on the patterns, trends, and exceptions found through data exploration to support the business. It is also known as data harvesting.
Data mining is also a technique using software tools geared for the user who typically does not know exactly what he’s searching for, but is looking for particular patterns or trends. Data mining is the process of sifting through large amounts of data to produce data content relationships. This is also known as data surfing.
In a large data warehouse implemented by a business organization, it may be very difficult to retrieve relevant data from among the high volume of data coming from a variety of disparate data sources. Data mining can help a data consumer within the organization in sorting through the high volume of data and use this data in conjunction with the company’s business intelligence system in order to spot trends and patterns to be used in decision making.
Software application solution for data mining allows data consumers to analyze data from many dimensions, perspectives and angles. These software applications categorize data and summarize all identified relationships. From a technical view, data mining is the process of spotting patterns and correlations among the hundreds of fields in large relational databases. Today’s data mining applications try to leverage the processing power and disk storage capacity of computers as well as the high end network infrastructures.
Data can help all kinds of business organizations determine strong and weak points in their business operation so they can formulate strategic ways to gain a competitive edge against their competitors.
For example, a grocery is using a data mining software application so it can analyze buying patterns in a certain locality. The d grocery discovers that when men buy baby diapers on Monday and Sunday, they also buy beer. The data mining software analysis tool also reveals the usual day men do their weekly grocery on a Sunday.
The grocery could then formulate selling strategy to optimize their sales bases on the shopping pattern of this particular market. One strategy would be to move similar products that go with beer (for instance, food items that go well with beer) and diapers and make sure that both beer and diaper are sold at full price on Mondays. Without the use of data mining and some analysis tool, the grocery would have no idea the relationship between beer and diaper!
Data mining is a relatively new term but the technology behind it is not. Data mining makes extensive use of metadata, a data about other data. For a long time, many companies have been using computer technology in order to sift thorough very high volumes of data such as those used in supermarket scanners and produce market research reports.
Today’s data mining technology even goes beyond trend spotting and simple analysis. It can even identify very important attributes of business processes and target opportunities with the help of complex algorithm.
Data mining is not just used in the business community. It is also used by government agencies such as in their census activities. Today, as the internet advances exponentially every day, the volume of data will surely rise to astronomic levels. Data mining technology will definitely evolve as well to handle more and more data.