Chapter 2

Identify which ETL tasks would be considered "Validating" the data, and which would be considered "Cleaning" the data.

1. Compare the number of records that were extracted to the number of records in the source database. Validating 2. Remove headings or subtotals. Cleaning 3. Remove leading zeroes and nonprintable characters. Cleaning 4. Compare descriptive statistics for numeric fields. Validating 5. Format negative numbers. Cleaning 6. Compare string limits for text fields. Validating 7. Correct inconsistencies across data, in general. Cleaning

For each of the six questions suggested by the Institute of Business Ethics to evaluate data privacy, categorize each question into one of these three types:

1. Does the company assess the risks linked to the specific type of data the company uses? Evaluate the company's use or misuse of the data. 2. Does the company send a privacy notice to individuals when their personal data are collected? Evaluate the company's use or misuse of the data 3. How does the company use data, and to what extent are they integrated into firm strategy? Evaluate the company's purpose of the data 4. Does our company conduct appropriate due diligence when sharing with or acquiring data from third parties? Evaluate the due diligence of the company's data vendors in preventing misuse of the data 5. Does the company have the appropriate tools to manage the risks of misuse? Evaluate the company's use or misuse of the data 6. Does the company have safeguards in place to mitigate these risks of misuse? Evaluate the company's use or misuse of the data

Match the relational database function to the appropriate relational database term:

1. Serves as a unique identifier in a database table. Primary keys 2. Creates a relationship between two tables. Foreign key 3. Two foreign keys from the tables that it is linking combine to make up a unique identifier. Composite primary key 4. Describes each record with characteristics with actual business information. Descriptive attributes 5. A means of storing data to ensure data is complete, redundant, to help enforce business rules. Relational database

Match each ETL task to the stage of the ETL process:

1. Use SQL to extract data from the source database. Obtain 2. Remove headings or subtotals. Clean 3. Choose which database and specific data will be needed to address the accounting question. Determine purpose 4. Compare the number of records extracted to the number of records in the source database. Validate 5. Make sure all data formats start with two capital letters. Fix inconsistencies. Clean 6. Input the data into the analysis tool. Load

Which of the following are useful, established characteristics of using a relational database?

Completeness Yes Reliable No No redundancy Yes Communication and integration of business processes Yes Less costly to purchase No Less effort to maintain No Business rules are enforced Yes

What are attributes that exist in a relational database that are neither primary nor foreign keys?

Descriptive attributes

The advantages of storing data in a relational database include which of the following?

Help in enforcing business rules and integrating business processes.

Which of the following describes part of the goal of the ETL process?

Identify and obtain the data needed for solving the problem.

Why is Supplier ID considered to be a primary key for a Supplier table?

It contains a unique identifier for each supplier.

The purpose of transforming data is:

to validate the data for completeness and integrity.