Data Mining Exercise 2: Analytics Data Environment

DAT 220: Module Two Exercise Guidelines and Rubric

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 Prepare a 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?

Guidelines Assignment must follow these formatting guidelines: double spacing, 12-point Times New Roman font, one-inch margins, and APA citations. Page length requirements: 1–2 pages.

Rubric

Critical Elements Exemplary (100%) Proficient (85%) Needs Improvement (55%) Not Evident (0%) Value

Source Data Systems Meets “Proficient” criteria and includes a process that can be extended to determine if other data sources might have utility to a customer data mining exercise

Two source data systems identified. Evidence is offered to support the utility of that data in a customer analytics exercise

One source data system is identified. Evidence is offered to support the utility of that source in a customer analytics exercise

No source data systems are identified

25

Data Warehouse Meets “Proficient” criteria and includes a process to determine other data sources and subject areas to include in a data warehouse

Description includes references to both sources and data subject areas

Description includes only references to sources or subject areas, but not both

No description is provided 25

Data Mart Meets “Proficient” criteria and contains a description of the relevance in determining the maturity of the data mart maintenance process

Description includes both benefits and limits of a data mart built specifically to support customer mining

Description includes limits or benefits of building a dedicated data mart to support customer analytics, but not both

No description is provided 25

External Data Meets “Proficient” criteria and contains a description of the relevance of external data sources to the customer analytics data mart maintenance process

External data source identified. Benefit of the data source and challenges posed by the data source are both described

External data source identified. Benefit of the data source or challenges posed by the data source are described, but not both

No external data source is identified

25

Earned Total 100%