Today's economy is characterized by a large and continuous flow of data. The ability to collect, analyze and use data to benefit your business is an invaluable asset. The process of compiling and organizing data into a common database is data warehousing. The data mining process relies on the data compiled in the data ware housing phase to detect meaningful patterns. Say no to plagiarism. Get a tailor-made essay on "Why Violent Video Games Shouldn't Be Banned"? Get an Original Essay A data warehouse is a database used to store data. It is a central data repository where data from various sources is stored. This data warehouse is then used for reporting and data analysis. It can be used to create trend reports for senior management reporting such as annual and quarterly comparisons. The purpose of a data warehouse is to provide the user with flexible access to data. Data warehousing generally refers to the combination of many different databases across an entire company. Data warehousing emphasizes the acquisition of data from multiple sources for useful analysis and access, but generally does not start from the perspective of the end user who may need access to specialized, sometimes local, databases. This last idea is known as a data mart. There are two approaches to data warehousing, top down and bottom up. The top-down approach creates data marts for specific groups of users after the complete data warehouse has been created. The bottom-up approach first creates data marts and then combines them into a single, all-encompassing data warehouse. Typically, a data warehouse is hosted on an enterprise mainframe server or, increasingly, in the cloud. Data from various Online Transaction Processing (OLTP) applications and other sources is selectively extracted for use by analytical applications and user queries. The term data warehouse was coined by William H. Inmon, known as the father of data warehousing. Inmon described a data warehouse as a subject-oriented, integrated, time-varying, non-volatile collection of data that supports management decision making. Data Mining is actually the analysis of data. It is the computer-aided process of exploring and analyzing huge sets of data that have been compiled by the computer or have been entered into the computer. In data mining, the computer will analyze the data and extract meaning from it. It will also look for hidden patterns within the data and attempt to predict future behavior. Data Mining is mainly used to find and show relationships between data. The purpose of data mining, also known as knowledge discovery, is to allow companies to visualize these behaviors, trends and/or relationships and be able to factor them into their decisions. This allows companies to make proactive, knowledge-based decisions. The term "data mining" comes from the fact that the process of data mining, or finding relationships between data, is similar to mining and searching for valuable materials. Data mining tools use artificial intelligence, machine learning, statistics, and database systems to find correlations between data. These tools can help answer business questions that traditionally took too long to answer. Data mining includes various phases, including the raw analysis phase, database and data management aspects, data preprocessing, model and inference considerations, metrics of interest, complexity considerations, post-processing. processing of discovered structures, visualization and online updating. In data mining, association rules come.