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Database Applications

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LP3 Assignment: Database Applications | Amy Bedard | | MT3500 | 10/24/2015 |

A data warehouse is a relational database that is designed to help companies analyze data. It usually contains historical data derived from transaction data, but it can include data from other sources. Data warehouses are defined by subject matter and they enable an organization to consolidate data from several sources. They have the ability to hold multiple subject areas of very detailed information that works to integrate all data sources. A data warehouse environment also includes an extraction, transportation, transformation, and loading (ETL) solution, an online analytical processing (OLAP) engine, client analysis tools, and other applications that manage the process of gathering data and delivering it to business users.
A data mart is a simple form of a data warehouse that is focused on a single subject or area of a company such as Sales, Finance, or Marketing. Data marts are often built and controlled by a single department within an organization. The sources could be internal operational systems, a central data warehouse, or external data. Compared to a data warehouse, a data mart often holds a single subject area of summarized information that concentrates on integrating information from one particular subject area.
Data mining is the practice of automatically searching large stores of data to discover patterns and trends that go beyond simple analysis of data warehouses or data marts. Data mining is used to simplify and summarize the data in a manner that can be understood, and then allow assumptions to be made about specific cases based on the patterns observed. Data mining uses mathematical algorithms to divide the data and evaluate the probability of future events. It automatically discovers patterns, predicts likely outcomes, creates action based

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