An Overview of Data Mining and Warehousing – Architecture, Techniques and Applications

Data mining is the process of extract in patterns from data. As more data is gathered, with the amount of data doubling every three years, data mining is becoming an increasingly important tool to transform these data into information. It is commonly used in a wide range of profiling practices, such as marketing, surveillance, fraud ddetection and scientific discovery. The term data mining has also been used in a related but negative sense, to mean the deliberate searching for apparent but not necessarily representative patterns in large numbers of data. To avoid confusion with the other sense, the terms data dredging and data snooping are often used. The data warehouse contains data from most or all of an organization's operational systems and this data is made consistent. Data in the data warehouse is never over-written or deleted- once committed, the data is static, read-only, and retained for future reporting. Top-down data warehousing, has defined a data warehouse as a centralized repository for the entire Enterprise. Bottom – up data warehousing, is a proponent of an approach to data warehouse design frequently