Assignment 3: Business Intelligence and Data Warehouses

Due Week 9 

Businesses today are extremely reliant on large amounts of data for making intelligent business decisions. Likewise, the data warehouses are often structured in a manner that optimizes processing large amounts of data.

Write a two to three (2-3) page paper in which you:

Your assignment must follow these formatting requirements:

The specific course learning outcomes associated with this assignment are:

Click here to view the grading rubric for this assignment.

 GRADING FOR THIS ASSIGNMENT WILL BE BASED ON ANSWER QUALITY, LOGIC / ORGANIZATION OF THE PAPER, AND LANGUAGE AND WRITING SKILLS, USING THE FOLLOWING RUBRIC.

Points: 100

Assignment 3: Business Intelligence and Data Warehouses

Criteria

Unacceptable

Below 60% F

Meets Minimum Expectations

60-69% D

Fair

70-79% C

Proficient

80-89% B

Exemplary

90-100% A

1. Outline the main differences between the structure of a relational database optimized for online transactions versus a data warehouse optimized for processing and summarizing large amounts of data.

Weight: 21%

Did not submit or incompletelyoutlined the main differences between the structure of a relational database optimized for online transactions versus a data warehouse optimized for processing and summarizing large amounts of data.

Insufficiently outlined the main differences between the structure of a relational database optimized for online transactions versus a data warehouse optimized for processing and summarizing large amounts of data.

Partially outlined the main differences between the structure of a relational database optimized for online transactions versus a data warehouse optimized for processing and summarizing large amounts of data.

Satisfactorily outlined the main differences between the structure of a relational database optimized for online transactions versus a data warehouse optimized for processing and summarizing large amounts of data.

Thoroughly outlined the main differences between the structure of a relational database optimized for online transactions versus a data warehouse optimized for processing and summarizing large amounts of data.

2. Outline the main differences between database requirements for operational data and for decision support data.Weight: 21%

Did not submit or incompletelyoutlined the main differences between database requirements for operational data and for decision support data.

Insufficiently outlined the main differences between database requirements for operational data and for decision support data.

Partially outlined the main differences between database requirements for operational data and for decision support data.

Satisfactorily outlined the main differences between database requirements for operational data and for decision support data.

Thoroughly outlined the main differences between database requirements for operational data and for decision support data.

3. Describe three (3) examples in which databases could be used to support decision making in a large organizational environment.

Weight: 21%

Did not submit or incompletelydescribed three (3) examples in which databases could be used to support decision making in a large organizational environment.

Insufficiently described three (3) examples in which databases could be used to support decision making in a large organizational environment.

Partially described three (3) examples in which databases could be used to support decision making in a large organizational environment.

Satisfactorily described three (3) examples in which databases could be used to support decision making in a large organizational environment.

Thoroughly described three (3) examples in which databases could be used to support decision making in a large organizational environment.

4. Describe three (3) examples in which data warehouses and data mining could be used to support data processing and trend analysis in large organizational environment.

Weight: 21%

Did not submit or incompletelydescribed three (3) examples in which data warehouses and data mining could be used to support data processing and trend analysis in large organizational environment.

Insufficiently described three (3) examples in which data warehouses and data mining could be used to support data processing and trend analysis in large organizational environment.

Partially described three (3) examples in which data warehouses and data mining could be used to support data processing and trend analysis in large organizational environment.

Satisfactorily described three (3) examples in which data warehouses and data mining could be used to support data processing and trend analysis in large organizational environment.

Thoroughly described three (3) examples in which data warehouses and data mining could be used to support data processing and trend analysis in large organizational environment.

5. 3 references

Weight: 6%

No references provided

Does not meet the required number of references; all references poor quality choices.

Does not meet the required number of references; some references poor quality choices.

Meets number of required references; all references high quality choices.

Exceeds number of required references; all references high quality choices.

6. Clarity, writing mechanics, and formatting requirements

Weight: 10%

More than 8 errors present

7-8 errors present

5-6 errors present

3-4 errors present

0-2 errors present

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