¶ … data collection mentioned earlier. This report shall focus on the data collection in particular. Within this report, there shall be a recitation of the data collection approach, a definition of the proper data collection channels, a description and depiction of the purchase of external data sets to assist in the problem, the development and description of data quality and other data governance issues and a planning of the ongoing storage and maintenance of the data. While planning and execute data analytics is not rocket science, as they say, it is something that is very important and needs to be done right the first time. The author of this report knows that a ten million dollar investment is not insignificant. As such, there should be a proceeding with caution yet expediency. As noted in the prior project, JC Dollar is in the right general area of analysis but is obviously not properly discerning the effects and outcomes as is needed to craft a good loyalty. The data collection for the customer loyalty project needs to be thorough but it cannot be obvious that the data collection is going on or what it is for. Given that, the best way to collect and harvest the information is to get the information from the shopping and buying habits of the customer. As much as can be collected with no direct feedback from the customer should be the norm. Additionally, the information then needs to be assembled and cultivated in the proper way...
The purchase of external data sources is absolutely not a bad idea as it can reveal things that JC Dollar's data would never reveal on its own. While JC Dollar's data would be informative and helpful, getting a wider industry picture would be better. This is because some of those other stores are doing much more correctly and thus their data would be more illuminating and helpful. As noted in the prior assignment, JC Dollar's assumptions and analysis of its customer and what that should mean in terms of how the loyalty program is structured has been wrong. As such, JC Dollar should look at data sets where the reactions were correct and the outcomes were positive (Corrigan, Craciun, Powell, 2014).
Data Mining Businesses can receive many benefits from data mining. Which benefits they receive, however, can also depend on the way in which their data mining is undertaken. Predictive analytics are used to understand customer behavior, and businesses use the behavior of the customer in the past to attempt to determine what the customer will do in the future (Cabena, et al., 1997). While it is not an exact science, many
Data mining, a process that involves the extraction of predictive information which is hidden from very large databases (Vijayarani & Nithya,2011;Nirkhi,2010) is a very powerful and yet new technology having a great potential in helping companies to focus on the most important data in their data warehouses. The use of data mining techniques allows for the prediction of trends as well as behaviors thereby allowing various businesses to make proactive
Data Mining Determine the benefits of data mining to the businesses when employing: Predictive analytics to understand the behaviour of customers "The decision science which not only helps in getting rid of the guesswork out of the decision-making process but also helps in finding out the perfect solutions in the shortest possible time by making use of the scientific guidelines is known as predictive analysis" (Kaith, 2011). There are basically seven steps involved
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
The ability to parse through the many records of transactions, customer contacts, and many other items stored electronically creates the foundation for data mining's definition. Data mining specifically is defined as the process of data selection, exploration and building models using vast data stores to uncover previously unknown patterns, insights, and observations that lead to strategies for effective differentiation and growth. Central to the development of data modeling is the creation of data and prediction models based
All of these factors combined to form the catalyst of the data warehouse project being made a higher priority than the many other competing projects within Wal-mart at the time. At a cost of approximately $3M in software and $9M in services and training, Wal-Mart partnered with Hewlett-Packard and became one of the first companies to adopt the HP Neoview data warehousing system. One of the key reasons for Wal-Mart
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