Data Mining

Introduction:

      Data mining, the extraction of hidden predictive information from large databases, is a powerful new technology with great potential to help companies focus on the most important information in their data warehouses. Data mining tools predict future trends and behaviors, allowing businesses to make proactive, knowledge-driven decisions. The automated, prospective analyses offered by data mining move beyond the analyses of past events provided by retrospective tools typical of decision support systems. Data mining tools can answer business questions that traditionally were too much time consuming to resolve. They drill down databases for hidden patterns, finding predictive information that experts may miss because it lies outside their expectations. Data mining also helps for content management systems that manage the process of gathering data, transforming it into useful, actionable information, and delivering it to business users.

Benefits:

Marketing / Retail:

• Data mining helps marketing companies build models based on historical data to predict who will respond to the new marketing campaigns such as direct mail, online marketing campaign etc. 
• Through the results, marketers will have an appropriate approach to selling profitable products to targeted customers.

Finance / Banking:

• Data mining gives financial institutions information about loan information and credit reporting. 
• By building a model from historical customer’s data, the bank, and financial institution can determine good and bad loans. 
• In addition, data mining helps banks detect fraudulent credit card transactions to protect credit card’s owner.

Manufacturing:

• By applying data mining in operational engineering data, manufacturers can detect faulty equipment and determine optimal control parameters.
• Data mining has been applying to determine the ranges of control parameters that lead to the production of the golden wafer. 
• Then those optimal control parameters are used to manufacture wafers with desired quality.

Government:

• Data mining helps government agency by digging and analyzing records of the financial transaction to build patterns that can detect money laundering or criminal activities.

Challenges:

There are so many challenges faced by software development companies regarding data mining as follow:

Privacy Issues:

• The concerns about the personal privacy have been increasing enormously recently especially when the internet is booming with social networks, e-commerce, forums, blogs etc.
• Because of privacy issues, people are afraid of their personal information is collected and used in an unethical way that potentially causing them a lot of troubles. 
• Businesses collect information about their customers in many ways for understanding their purchasing behaviors trends. 
• However, businesses don’t last forever, some days they may be acquired by other or gone.
• At this time, the personal information they own probably is sold to other or leak.

Security Issues:

• Security is a big issue. Businesses own information about their employees and customers including social security number, birthday, payroll and etc. 
• However how properly this information is taken care is still in questions. 
• There have been a lot of cases that hackers accessed and stole big data of customers from the big corporation such as Ford Motor Credit Company, Sony etc. with so much personal and financial information available, the credit card stolen and identity theft become a big problem.

Misuse of information:

• Information is collected through data mining intended for the ethical purposes can be misused.
• This information may be exploited by unethical people or businesses to take benefits of vulnerable people or discriminate against a group of people.

Conclusion:

Data mining is an important part of knowledge discovery process that we can analyze an enormous set of data and get hidden and useful knowledge.  This concept is very useful to all software development companies in India.