What is the difference between data mining and data storage?
Data mining conditions and data stores are often confused by business and technical staff. The entire data management area has experienced phenomenal growth with the implementation of software programs for data collection and reduced computer memory costs. The primary purpose of both functions is to provide tools and methodologies to explore formulas and importance in large amounts of data. Data mining is to use the logic of patterns recognition for identity trends within a sample data set and extrapolates this information against a larger data fund. Data storage is the process of extraction and storage to allow easier reports.
Data mining is a general term used to describe a number of business processes that derive data patterns. Usually, the SPE is used to identify the software package Statistical analysis patterns based on a set of data and queries generated by an end user. Typical use of data mining is to create targeted marketing programs, identification of financial fraud and designation of unusual formulas in RA behaviormci security.
Example of data mining is the process used by telephone companies to introduce products on existing customers. The telephone company uses data mining software to access its customer information database. A question is written to identify customers who have subscribed to the basic telephone package and internet services in a specific time frame. Once this data set is selected, another question is written to find out how many of these customers have used free other phone features during the test. The results of this data mining exercise reveal behavior patterns that can manage or help improve the marketing plan to increase other telephone services.
It is important to realize that the primary purpose of mining is to find out the formulas in the data. Specifications used to define a sample set have a huge impact on the importance of outputOst analysis. Returns to the above example, if the data set is limited to customers in a particular geographical area, the results and formulas will differ from a wider data set. Although both data mining and data warehouse work with large volumes of information, the processes used are quite different.
The data warehouse is a software product that is used to store large volumes of data and operate specially designed queries and messages. Business Intelligence is a growing area of study that focuses on data storage and related functions. These tools are designed to extract data and store them by a method designed to provide increased system performance. Most terminology in data mining and data sharing is the same, leading to greater confusion.