The flattened paradigm of a data warehouse database allows for significantly faster select statements to be run against the database. Unlike most user-facing database queries, most data mining queries are highly complex and most work through a massive amount of data. Whereas a user-facing query usually takes less than a second to process, a data mining query may take hours. It is important to reduce the amount of time and processing required for data mining in order to keep costs down.
When used correctly, data warehousing and data mining can lead businesses to massive profits and savings. A retailer can gain detailed knowledge about what products are most likely to be the most sought after in specific regions. A car manufacturer can accurately predict the lifespan of a vehicle component and issue a pre-emptive notice or recall. Hospitals and medical services can begin to gain a big-picture view of the profile of a person who will suffer from a major illness. As mentioned by Hormazi and Giles (2004), data warehousing and data mining can effectively be utilized to help identify potential fraud and to help with risk management.
In order to more effectively pull desired data from a data warehouse, views are created. A view is a database element that has data in from an existing query. A query can be turned into a view and then that view referenced just like any other table in the database. The difference is that the data pulled from a view will be dynamic and current based on the current data in the database. A fact table in a data warehouse is likely to have a great deal more information in it than is required by any one process or any one report. For instance, an analyst at Honda may only be interested in sales data and not maintenance information. Or a manager may wish to run forecasts every month based on the previous four months. Since these subsets of data are to be used again and again, it makes sense to place them in views that will be available for those purposes.
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. ...
Data Mining can help to find trends about the way users access the CTI website. ... 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. ... In prediction, historical data is used to build a predictive model that explains the current observed behavior. ...
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. ...
However, due to some negative effects of mining in our natural environment, anti-mining groups began to form. ... Responsible mining is mining which follows the laws set by our government. ... The benefits from responsible mining done by mining companies do not stop there. ... It would be better if these small-scale mining operations are taken over by large-scale mining operations. ... They should know how to distinguish between the effects of small-scale mining and responsible 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). ...
