Data Mining

Data Mining is gradually becoming a popular concept, as a business management tool, where large amount of data and picking out relevant information is expected to reveal knowledge structures that can guide decisions in conditions of narrow certainty. The term is usually used to explain software that doesn’t just change the presentation but actually discovers formerly unknown associations with the data. Data mining serves as an automated tool that uses several complex computational techniques, to perform logical functions, characterising large data sets with one or more data sources and identifying significant patterns, trends, and relationships not easily detected through traditional analytical techniques alone. It involves exploring business transactions and financial analysis, but is more often being used in the science and mathematical fields to extract information from huge data generated by modern experimental and observational methods. Data mining software can also help retail companies find customers with common interests.

Data mining can be done manually by cutting and dicing the data until a pattern becomes clear. Data mining software is separated into two groups: data mining tools and data mining applications. Data mining tools provide a number of methods that can be applied to any business problem. Data mining applications, on the other hand, implant techniques inside an application modified to address a specific business problem. Both data mining tools and data mining applications are essential Hence, many organizations are using data mining tools and data mining applications together in an integrated environment for extrapolative analytics. Data mining tools are used to increase effectiveness of data mining applications. It also ensures flexibility, accuracy, and the delivery of best results possible.

Data mining work consists of five major essentials:
Extort, convert and load transaction data onto the data warehouse system.
Store and manage the data in a multiple database system.
Provide data access to business market analyst and information technology professionals.
Examine the data by application software.
Present the data in a useful format, such as a graph or table.

The two data mining techniques, Text mining and Web mining have led to the newest and hottest trends in data mining. These two data mining technologies have opened a rich streak of customer data in the form of textual comments from survey and log files and from Web servers, which were previously unusable. A data miner is a program that collects such information, without the user's knowledge, as spyware.

Data mining includes following factors:
Looking for patterns where one event is associated to another event
Finding and visually clustering groups of facts which were not known earlier.
Looking for sequences of patterns where one event leads to another later event
Looking for new patterns which may result in a change in the way the data is organized.

Data mining plays a critical role in decision making because they disclose areas of business improvement. Using data mining, organizations can increase the profitability, boost sales, detect fraud, smoothening interactions with the customers and improve risk management. The patterns revealed using data mining help organizations make better and prompt decisions.