Welcome to the The Physical Design Process MCQs Page

Dive deep into the fascinating world of The Physical Design Process with our comprehensive set of Multiple-Choice Questions (MCQs). This page is dedicated to exploring the fundamental concepts and intricacies of The Physical Design Process, a crucial aspect of Data Warehousing and OLAP. In this section, you will encounter a diverse range of MCQs that cover various aspects of The Physical Design Process, from the basic principles to advanced topics. Each question is thoughtfully crafted to challenge your knowledge and deepen your understanding of this critical subcategory within Data Warehousing and OLAP.

Check out the MCQs below to embark on an enriching journey through The Physical Design Process. Test your knowledge, expand your horizons, and solidify your grasp on this vital area of Data Warehousing and OLAP.

Note: Each MCQ comes with multiple answer choices. Select the most appropriate option and test your understanding of The Physical Design Process. You can click on an option to test your knowledge before viewing the solution for a MCQ. Happy learning!

The Physical Design Process MCQs | Page 6 of 9

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OLAP in the Data Warehouse 🔒

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Data Warehousing and the Web 🔒

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Data Mining Basics 🔒

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Growth and Maintenance

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Important Terms and Definitions

Q51.

What should be considered when determining the maximum number of indexes per table in a data warehouse?

The size of the table

The simplicity of the table structure

The frequency of table updates

The number of foreign keys in the table

Discuss

Answer: (a).The size of the table Explanation:The maximum number of indexes per table in a data warehouse varies inversely with the size of the table.

Q52.

Why does the loading of data into a data warehouse slow down when there are a large number of indexes?

Indexes improve loading speed

Index entries must be created for each record during loading

Indexes are not used during the loading process

Loading speed is not affected by indexes

Discuss

Answer: (b).Index entries must be created for each record during loading Explanation:When there are many indexes, creating index entries for each record during loading slows down the data loading process.

Q53.

What is the default indexing method in most database management systems?

Bitmap index

Clustered index

B-Tree index

Hash index

Discuss

Answer: (c).B-Tree index Explanation:The default indexing method in most database management systems is the B-Tree index.

Q54.

Why is the B-Tree index technique considered superior to other indexing techniques?

It requires less storage space

It provides faster data retrieval, ease of maintenance, and simplicity

It works well with low-selectivity columns

It is suitable only for read-only tables

Discuss

Answer: (b).It provides faster data retrieval, ease of maintenance, and simplicity Explanation:The B-Tree index technique is considered superior due to its fast data retrieval, ease of maintenance, and simplicity.

Q55.

What is the selectivity of a column in a table?

The total number of unique values in the column

The ratio of the number of unique values to the total number of values in the column

The frequency of updates to the column

The size of the column in bytes

Discuss

Answer: (b).The ratio of the number of unique values to the total number of values in the column Explanation:The selectivity of a column is the ratio of the number of unique values to the total number of values in the column.

Q56.

In a B-Tree index, what type of column is most suitable?

Columns with low selectivity

Columns with high selectivity

Columns with concatenated values

Columns with numeric data types

Discuss

Answer: (b).Columns with high selectivity Explanation:B-Tree indexes are most suitable for highly selective columns, where the values at the leaf nodes are unique.

Q57.

What can be done to improve the selectivity of a non-highly selective column for B-Tree indexing?

Create a clustered index

Create a composite index

Create a hash index

Concatenate the column with another column with higher selectivity

Discuss

Answer: (d).Concatenate the column with another column with higher selectivity Explanation:To improve the selectivity of a non-highly selective column for B-Tree indexing, you can concatenate the column with another column with higher selectivity.

Q58.

What is a bitmap index?

An index technique suitable for high-selectivity columns

An index technique suitable for low-selectivity columns

An index technique that combines data and index segments

An index technique that supports only read-only tables

Discuss

Answer: (b).An index technique suitable for low-selectivity columns Explanation:A bitmap index is an index technique suitable for low-selectivity columns.

Q59.

How is a bitmap index constructed for a column with distinct values?

Each entry in the bitmap contains one bit for each distinct value, and the bit is set to 1 if the value is present

Each entry in the bitmap contains one byte for each distinct value, and the byte is set to the ASCII code of the value

Each entry in the bitmap contains one character for each distinct value, and the character represents the value

Each entry in the bitmap contains one integer for each distinct value, and the integer is set to 0 if the value is present

Discuss

Answer: (a).Each entry in the bitmap contains one bit for each distinct value, and the bit is set to 1 if the value is present Explanation:Each entry in a bitmap contains one bit for each distinct value, and the bit is set to 1 if the value is present.

Q60.

In a bitmapped index, how is the result set determined for a query with multiple predicates?

By using a balanced binary tree

By applying Boolean logic to the ordered bits in the bitmapped indexes

By constructing a hash table

By using a sequential scan of the data table

Discuss

Answer: (b).By applying Boolean logic to the ordered bits in the bitmapped indexes Explanation:The result set in a bitmapped index for a query with multiple predicates is determined by applying Boolean logic to the ordered bits in the bitmapped indexes.

Page 6 of 9

Building Blocks of Data Warehouse 🔒

Trends in Data Warehousing 🔒

Planning and Project Management 🔒

Requirements as the Driving Force for Data warehousing 🔒

Architectural Components 🔒

Infrastructure as the Foundation for Data Warehousing 🔒

Role of Metadata in Data Warehousing 🔒

Advanced Topics in Dimensional Modeling 🔒

Data Extraction,Transformation and Loading 🔒

OLAP in the Data Warehouse 🔒

Data Warehousing and the Web 🔒

Data Mining Basics 🔒

Data Warehouse Deployment 🔒

Welcome to the The Physical Design Process MCQs Page

The Physical Design Process MCQs | Page 6 of 9

Explore more Topics under Data Warehousing and OLAP

The Compelling Need for Data Warehousing

Defining the Business Requirements

Principles of Dimensional Modeling

Importance of Data Quality

Matching Information to the Classes of Users

Growth and Maintenance

Important Terms and Definitions

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