Technically, data mining is the process of finding correlations or patterns among dozens of fields in large relational databases" (Palace, 1996).
One common example of using data mining is that of store inventory, such as a Midwest grocery chain called Kroger that used the data mining capacity software to discover: "that when men bought diapers on Thursdays and Saturdays, they also tended to buy beer. Further analysis showed that these shoppers typically did their weekly grocery shopping on Saturdays. On Thursdays, however, they only bought a few items. The retailer concluded that they purchased the beer to have it available for the upcoming weekend. The grocery chain could use this newly discovered information in various ways to increase revenue. For example, they could move the beer display closer to the diaper display. and, they could make sure beer and diapers were sold at full price on Thursdays" (Palace, 1996)
The pairing of promotions is especially useful in the food industry, where consumers are often very price sensitive, and there is a wide variety of substitutes. For example, a chain such as McDonald's when attempting to launch a new line of healthier salads might discover that the customers that consume salads most often purchase Happy Meals as well, indicating they are mothers going...
Data Warehousing and Data Mining Executive Overview Analytics, Business Intelligence (BI) and the exponential increase of insight and decision making accuracy and quality in many enterprises today can be directly attributed to the successful implementation of Enterprise Data Warehouse (EDW) and data mining systems. The examples of how Continental Airlines (Watson, Wixom, Hoffer, 2006) and Toyota (Dyer, Nobeoka, 2000) continue to use advanced EDW and data mining systems and processes to streamline
The use of databases as the system of record is a common step across all data mining definitions and is critically important in creating a standardized set of query commands and data models for use. To the extent a system of record in a data mining application is stable and scalable is the extent to which a data mining application will be able to deliver the critical relationship data,
Modeling Tool In one of my system projects, I used the Logical Data Model to build separate models for each logical entity of the project. With Logical Data Model, it allowed me to represent each area of the system with one model diagram. Thus, the entire project encyclopedia is composed of separate data models that can be assembled into one complete system. Logical data modeling can meet the needs of every system
Modeling and Mental Practice There has been much research regarding modeling (also called observational learning) and mental practice, also -- and perhaps more commonly -- known as imagery. Mental practice is also known as mental rehearsal and visuo-motor rehearsal, although these terms are much less commonly used in the literature assessed here. The current research question is: Does modeling, when combined with mental practice and physical practice, have a grater effect than
Data Warehousing: A Strategic Weapon of an Organization. Within Chapter One, an introduction to the study will be provided. Initially, the overall aims of the research proposal will be discussed. This will be followed by a presentation of the overall objectives of the study will be delineated. After this, the significance of the research will be discussed, including a justification and rationale for the investigation. The aims of the study are to
Modeling Mitosis Structured Investigation Inquiry: Modeling Mitosis Students will be required to understand the process of mitosis and demonstrate this by drawing pictures of the different mitotic stages in the correct temporal order. These drawings will be judged by how complete they are. For example, the subcellular organelles involved in each stage, including the nuclear membrane, chromosomes, spindle fibers, and centrioles, should be clearly labeled and depicted in a manner that reflects
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