Fact less Fact tables are used a) For event trackingb) For handling multi valued dimensionsc) As a helper tabled) None of the above

Metadata is associated with the followinga) Extraction Transformation and Loadingb) Front end access c) Data warehouse administrationd) All of the above

The relationship between a fact table and a dimension table is

a) One to Oneb) One to Manyc) Many to Oned) Many to Many

A fact table is linked to a dimension table using

a) Surrogate keysb) Compound keysc) Complex keysd) None of the above

The following methods can be used for handling slowly changing dimensions

a) Inserting a new field in the tableb) Inserting a new record in the tablec) Overwrite the existing datad) All of the above

Which of the following is associated with coverage tables?

a) Factless fact tablesb) Conformed dimensionsc) Casual dimensionsd) Helper tables

How are dimensions in a Multi Dimensional database related?

a) Hierarchicallyb) In a Networkc) By an inverse list d) Non of the above

The process of standardizing the data that is extracted from the operational systems is known as

a) Transformationb) Cleansingc) Populationd) Data Staging

Which type of modeling technique is associated with a data warehousing?

a) Dimensional Modelingb) ER Modelingc) Object Oriented Modelingd) All of the above

Which of the following is not an ETL tool?a) Power Martb) Data Stagec) Scenariod) Data Junction

The process of viewing detailed data from summarized data is known as

a) Drill upb) Drill downc) Drill throughd) Drill across

Which one of the following is not an example of a measure?

a) Product costb) Product quantityc) Product named) Product price

How many techniques are there for handling slowly changing dimensions?

a) 1b) 2c) 3d) 4

Where will you find measures in a data warehouse?

a) Dimension tablesb) Fact tablesc) Helper tablesd) Look up tables

Which of the following statements are false?a) A collection of data warehouse will

equal a data mart.b) A data warehouse is used for making

tactical decisions.c) A data warehouse is updated by

transactions.d) All of the above.

When would you ideally use multiple fact tables?a) When all the fact can’t be place in a single

fact table.b) In order to support a business with many

process.c) In order to track multiple events.d) In order to support users that are located at

different locations and require high response times.

Which of the following statements are true for dimensional tables?

a) They are the entry points into the data warehouse.

b) Data in a dimension table should not change.c) Every dimension table should be linked to

only a single fact table.d) Dimension tables describe the data that is

stored in the fact table.

Which of the following statements are true for Snow Flake Schemas

a) It affects cross attribute browsing performance.

b) It should always be used in the design of a data warehouse.

c) It defeats the purpose of using bitmap indexes.

d) All of the above

When would you ideally use a type 3 Slowly Changing dimension (by adding an addition field)?

a) It is used when a change is tentativeb) When we want to keep the tracking history

with the old value of the attribute as well as the new.

c) When we want to save on storage space.d) It should be used when the old value of the

attribute is of no importance.

Which of the following statements are true for a star schema?

a) A star schema is highly normalizedb) It is built for simplicity and speed.e) The star schema is built for quick

access to the data.c) All of the above

Which of the following factors influence the ETL architecture?

a) The type of end user access tool that will be used.

b) The type of analysis that will be carried out on the data warehouse.

c) Volume at each data warehouse component.d) Complexity of the process at each stage.

What is the use of a data staging area?a) It serves as a storage area on which

end users can carry out analysis.b) A data staging area serves the same

purpose as an ODS.c) It serves as a storage area where the

source data can be prepared for loading into the data warehouse.

d) All of the above.

Which of the following is true for dimensional modeling?

a) It cannot be easily extended to accommodate unexpected new data elements.

b) It is a predictable and standard framework.c) It is difficult to design a data warehouse

based on a dimensional model.d) The framework of the star join schema

withstands unexpected changes in user behavior.

Which of the following is not true when it comes to dimensional modeling?

a) Implementing a dimensional data model will lead to a stovepipe decision support system.

b) Dimensional models only work with retail databases.

c) Snowflaking is an alternative to dimensional modeling.

d) All of the above

SECTION ID (PK)CourseNumber (FK) Section (FK)DaysTime

COURSE

CourseNumber (PK)

Title

STUDENT StudentID (PK)FName LName Major

ENROLLMENT StudentID (PK) (FK)ClassID (PK) (FK), Grade

1. List the CourseNumber, Section, Title, and Days taught for all sections starting at 6:30 PM. Sort alphabetically by Title.

2. List Section, Days, and Time for all sections of MIS 3353 that have at least 15 students enrolled.

3. List the CourseNumber, Title, and total count of students that meet on Monday (Days contains the character M). Group all Monday sections together for the count.

4. List the Name of all students who do NOT have a class on Wednesday (Days = W). List each student only once.

5. List StudentID for all students who are TCOM majors and have at most one grade of A.

1. SELECT course.CourseNumber, section.Section, course.Title

FROM course, section WHERE course.CourseNumber =

section.CourseNumber AND section.Time = ‘6:30 PM’ ORDER BY Title;

SELECT section.Section ,section.Days ,section.Time FROM section WHERE course.CourseNumber = ‘MIS

3353’ GROUP BY section.ID ,section.Days ,section.Time HAVING count(*) >= 15;