Abstract: This document discusses trends in data mining and data warehousing. It covers applications and new possibilities in the field along with the risks involved, limitations and possible questions about the ethical use of the information. With the increase in computing power in recent decades, the industry has found many innovative solutions to previously impossible problems. The sharp increase in computing power and the ability to push numbers and move large amounts of data in reasonable times have improved the capabilities and size of databases. Companies like NCR can now maintain databases larger than a terabyte. (So ​​1 Terrabyte = 1024 Gigabyte, 1 Gigabyte = 1024 Megabyte, 1 Megabyte = 1024 bytes. 1 Terrabyte is 1,099,511,627,776 bytes.) Of course the size is irrelevant to the database unless there is a mining time fast or a quick response time to data queries to the database. Oracle, Informix, and NCR are some data mining companies that provide rapid response to data queries on their databases and offer a new world of opportunities. Today, data mining can allow companies to create customer profiles, easily manipulate information, and provide knowledgeable access to the current state of their company. However, one reality that many companies discover the hard way is that data mining and data warehousing don't work for them. As with many new tools or technologies, companies may jump on the bandwagon without contemplating its potential weaknesses. To remain competitive in today's business world, companies should consider implementing data warehouses, but only with adequate research that takes into account the benefits and weaknesses of such an initiative. Data mining has created new ways of moving information and has enabled new applications in using information. Any type of business will accumulate large amounts of data and statistics during their normal operations. The data includes vital information such as sales, overhead, distribution and chain locations, as well as information such as customer purchases, sales demographics and sales rate by store location. The sheer amount of information generated by even small businesses can be staggering. Before the advent of reliable data warehousing solutions, most information was discarded because there was no reasonable way to use it. However, Han, Urban, and Dasgupta point out that data mining can be used to find relationships between data that might appear unrelated.