Data Mining can help to find trends about the way users access the CTI website. Consider the visitor access patterns in the Programs and Courses sections. Limiting our attention to users who accessed the Programs section, we can perform classification analysis on users interested in Ph.D. programs versus Masters programs (including all Masters programs, Computer Science, Distributed Systems, etc). First we would separate those who were clicked a link into only Masters programs, and then separate those who clicked a link into only Ph.D. programs, and then separate out those who clicked links into both. We would also put into each of these groups, a list of links that the users clicked in the Courses section. Affinity grouping analysis using a powerful algorithm will show any patterns or general association rules between users who access the Ph.D. in the Program page and a specific Algorithm class. Data Discrimination analysis can allow us to compare users who click on the Ph.D. link in the Program page with those who clicked on the Master's links. We might find the group who click only on the Ph.D. link much more frequently and click on a link to the Algorithm class in the Courses section. We could use this knowledge to provide some cross-links within the Ph.D. program page showing users some courses like the Algorithm class that would be of interest. .
Examine the visitor's access pattern in the courses and the programs section. If we apply affinity grouping or in other words market basket analysis we may find very interesting pattern that students in telecommunication usually prefer to take non-programming courses. This may turn into cross selling idea, if we offer more and more non-programming course in telecom program, it may attract more student in this program who don't like to do programming. We can perform classification analysis on the users who is interested in Telecommunication program versus courses offer into Telecommunication program.
Successful Data Warehousing Many organizations today utilize data warehousing and data mining very successfully. ... The smartest user of data warehousing and data mining today is Amazon.com. ... One of these investments has been data warehousing and data mining. ... Another biggest users of Data warehousing and Data mining today is the United States Armed Forces. ... Views are a real must in data mining. ...
Data mining will not be enough to prevent terrorism in the U.S. ... Others are having many different emotions about data mining. ... The former program they had for data mining cost millions of dollars. ... In the article "Data Mining: The New Weapon in the War on Terrorism?" ... The fear in many people is if the government starts data mining so w...
A new, and important, tool in gaining this knowledge is Data Mining. Data Mining is a set of automated procedures used to find previously unknown patterns and relationships in data. ... "Without the pool of validated and scrubbed data that a data warehouse provides, the data mining process requires considerable additional effort to pre-process the data" (SAS Institute). ... Data Mining is largely, if not entirely used for business purposes. ... The applicability of these programs can accommodate the various uses of data mining. ...
Retail Data Sets Retail data is often placed into four basic categories. ... Data warehousing is the process of integrating enterprise wide corporate data into a single repository. ... A data delivery system, such as the data warehouse, has similar processes. ... Data Production Data production is the phase where data is first captured. ... Data Retailing The final step in the data delivery system is called "data retailing." ...
The importance of mining is definitely significant to Canada. Mining, is an important industry, and Canadians are very advanced in their mining technology, but during the mining process, there is certain level of pollution produced. ... Mining is very important in Canadian life. ... Through the use of advanced software, geological models can be produced from drill hole data. ... Mining, as we understanding, is a very important industry. ...
This kind of data-warehouse design is sometimes called an atomic data warehouse. The main purposes of an atomic data warehouse are to serve as a staging ground for subsets of the atomic warehouse, called data marts, and to serve as a reference data warehouse. ... These data marts are copied to other computers as data warehouses in their own right. Data marts may be as large as (or even larger than) the data warehouse that spawned them. ... Data marts are data warehouses built to meet particular user needs. ...
The defining characteristic of a database is (arguably) the data model that it implements. A data model is an abstract, logical definition of the objects used to model the structure of data and the operators used to model its behavior. ... The data is perceived by the user as tables (and nothing but tables); and 2. ... Multi-dimensional systems: Data is stored as a multi-dimensional array. ... Related topics are data warehousing and data mining. ...
Another important argument supporting math as a tool to predict human behavior is data mining because it has been used to detected customer purchasing patterns. ... Another way math is used to predict human behavior is through data mining. Business have used data mining to find out what products customers like to buy. ... Every grocery chain can benefit by using data mining to increase their profit. Wal-Mart uses excessive data mining from "over 2,900 stores in 6 countries" to increase its profit too (par. 11). ...
In our case, the domain is the set of all possible data instances. ... The Manhattan metric is widely used in a variety of data mining algorithms and is justified for those problem domains where it is desired that two data instances should be the same distance when they differ by, say, 4 units along 2 dimensions, as when they differ by 1 unit along one dimension and 3 along another The Power Distance is a generalization of the Minkowski metric discussed earlier: where the points take the form and . ... The Euclidean , Manhattan and Cosine Distances Compared Mahalanobis Measure ...
