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Overview
As organizations become more and more dependent on sophisticated data mining techniques to uncover new value streams, data management practices have been forced to respond to the often unique requirements presented by data mining professionals. It is self-evident that the organizations that best understand their data assets are also best positioned to adapt to the emerging data management practices required by data mining initiatives. In this exercise, you are asked to provide an overview of a prototypical company’s data environment and explain how it is situated for use in customer data mining activities.
Prompt
Assume you have been asked to present the current state of an organization’s analytic data assets.
Your Assignment
Depiction of an analytics data environment typical to an online retailer. Include a data warehouse repository that depicts various sources of available data. Also include at least one data mart that is sourced at least in part from the data warehouse.
The assignment will be graded based on the following critical elements:
a) Source Data Systems: Identify at least two source data systems that are typical to an online retailer and that might be useful to a data mining initiative to better understand the retailer’s customers.
b) Data Warehouse: Describe the contents of a data warehouse typical to an online retailer, emphasizing sources (transactional system, supply chain management system, etc.) and data subject areas (sales, customer, supply, etc.).
c) Data Mart: Identify the benefits and limitations of a data mart that is sourced from the warehouse to support customer analytics for a typical online retailer.
d) External Data: Identify a source of external data a typical online retailer might wish to include in a customer analytics data mart. What benefit is gained by the addition of this external data? What challenges are presented by the integration of this external data source?
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