Another Example

    

     Facebook is using the services of Datalogix, a US-based data-mining company that collects and analyses information about shoppers from brick-and-mortar stores, to gauge how many of its users make buying decisions based on the advertisements served on the social networking site.

     The move, seen to be Facebook's response to the growing pressure to prove its efficacy as an advertising platform, raises concerns among privacy advocates who wonder whether using Datalogix violates Facebook's $9.5 million settlement with the US Federal Trade Commission over privacy practices. The settlement requires the social networking site to make it clear to users when it shares their information beyond what their privacy settings mandate, operate a programme to protect users' privacy and get users' approval before sharing their information.Want know more?


Other Informations for Data Mining:
http://www.possibleworldwide.com/thoughts-ideas/why-companies-still-don%E2%80%99t-use-data-mining/ 

http://www.marketingwithmeaning.com/2011/01/12/why-companies-still-dont-use-data-mining/ 

http://www.dataminingblog.com/top-10-challenging-problems-in-data-mining/

Examples

     A successful example of putting data mining into the business process is the ompany, Google. Google is a large, multinational, and publicly-traded company that is built around its search engine. Its success of the search engine is mostly because of an algorithm named PageRank. PageRank is a program that ranks webpages according to the users’ search input. Google sees the potential of this and thinks that just having this one patent is not enough. So it started to have its own web browser and operating systems. Also, Google started its own email services named Gmail, and it bought the famous video website, YouTube. All of these services would collect data that is relevant to what the user has typed, and then it would predict what the user is looking for and rank the websites that would be most helpful to the user. Because Google has a lot of recourses for data mining, it is able to search from a greater amount of data, therefore increasing the chance of providing the information that the user really needs. Google has made a ton of money by using this strategy of data mining.

      Compared to Google, Yahoo is not doing as successful. Yahoo is also a multinational company that is known for its web search engines. However, it has a significantly fewer number of resources for data mining when comparing to Google. Therefore, its search engine is less powerful and less people use Yahoo.

 

     More examples of companies that smartly use data mining includes: Amazon, EBay, Capital One, etc. These companies have all generated large amount of profits with the help of data mining. It is obvious that the ability of data mining has been proven and it is very likely that more companies will adjust to this new technology.Learn More?

 

Data Mining in the Future

     Data mining has proven to predict accurate future trends, and it is very useful in decision making and helps to generate more profits for companies. But although it is an excellent tool for predicting customers' wants and requires, there are still numerous enterprises that did not account it as a part of their business process. These companies are concerned about the costs and risks of data mining, the lack of executive power, and alternative distribution of resources.

     Data mining is a fairly new technology in the world of computer science and only a number of big companies has adapted to its use. But the accurate predictions of data mining are able to bring us the correct information to make the right decisions. Because data mining is still new, there is a lot more of it that could be explored. As data mining progresses and becomes more common in the future, we can see that there will be a rise of number in the number of enterprises that include data mining into their business processes.
 

Advantages & Disadvantages

      Advantages/Benefit  

• Predict future trends, customer purchase habits
• Help with decision making

• Improve company revenue and lower costs
• Market basket analysis
• Fraud detection

       Disadvantages/Barriers

• User privacy/security
• Amount of data is overwhelming
• Great cost at implementation stage
•  Possible misuse of information
•  Possible in accuracy of data

 

Relationship with Companies

• Data mining analyzes data and summarizes it to extract useful information.
• It helps with identifying various groups in data. This leads to an accurate prediction, which in turn helps managers make the right decisions.
• It is useful to managers and companies because it can improve company revenue and help lower costs.

Welcome！

Hi, this is a data minning website for BUS237 D108

   
       We will introduce some aspects of data minning.

           
                Feel free to gain knowledge about DATA MINNING!
 

What is Data Mining?

     Data mining is using statistical techniques to find patterns and relationships among data for classifying and making predictions. Its purpose is to get knowledge from a great amount of data to predict future outcomes.

     Data mining is developed because the volume of data is in substantial amount and it is extremely difficult to process. These data could be trashed, but with computers, they are actually stored and are readily available for future use. Overtime, these data accumulates and has formed patterns and relationships. This is how data mining comes into place; they process these patterns to predict future outcomes and help to benefit the company. The most unique part of data mining is that it can gather information and data without even letting the users to know that this is taking place. Therefore, though data mining is useful and helpful for companies to generate more profits, it raises an ethical issue about user privacy.Learn More?