Database Design Quiz

How does Third Normal Form (3NF) Ming differ hom dimensional modeling in the context of database design?

• 3NF modeling is used to eliminate data redundancies and while dimensional modeling for transaction processing modeling is optimized for reporting and analysis

• 3NF modeling prioritizes data redundancy, whereas dimensional modeling seeks to simplify reporting and analysis

• INF modeling and dimensional modeling both aim to optimize transaction processing speed and efficiency design technique that

• Dimensional modeling captures micro relationships among data elements, resulting in a complex web of joins, unlike 3NF modeling.

Which of the following database models can be represented using Entity Relationship Diagrams (ERDs)

• Only Third Normal Form (BNF) models can be represented as ERDs because they focus on the relationships between database tables.

• Both Third Normal Form (3NF) and dimensional models can be represented in ERDs, despite their different structures

• Dimensional models cannot be represented using ERDs due to their lack of normalized structures

• ERDs are exclusive to dimensional models because they deal with the micro-relationships within the data

Why should fact tables in a dimensional model contain the lowest, most detailed atomic grain?

• To ensure that the fact tables are normalized to the highest normal form for optimal performance.

• To allow for the highest level of summarization and reduce the flexibility of querying the data.

• To enable queries to ask the most precise questions and allow details to be grouped in any way for ad hoc queries.

• To increase the complexity of the data model, making it more challenging to alter the data structure over time.

Which of the following is NOT a step in the process of converting from normalized structures to dimensional models?

• Designating many-to-many relationships in the normalized model as fact tables

• Normalizing fact tables to Third Normal Form (3NF) within the dimensional model.

• Denormalizing remaining tables into flat dimension tables with composite keys

• Removing related context from 3NF tables to create dimension tables.

Which of the following is NOT listed as an advantage of using surrogate keys in dimension tables within a data warehouse?

• Surrogate keys allow for tighter and more efficient joins, leading to better performance.

• They buffer data warehouse systems from operational key management practices that may change natural keys frequently.

• Surrogate keys enable the integration of disparate sources by providing a neutral key for mapping in the ETL system.

• They directly reduce the amount of disk space required for the data warehouse.

Which of the following is a characteristic requirement of dimension attributes in a dimensional table?

• Dimension attributes must be able to accept multiple values per row in the dimension table to allow for complex querying.

• Dimension attributes should be verbose, descriptive, complete, discretely valued, and quality assured.

• Dimension attributes are best left undefined to maintain the flexibility of the dimensional model.

• Dimension attributes should frequently contain null or missing values to save storage space

Why is a 4-byte integer commonly used as a surrogate key in database dimension tables?

• It makes a great surrogate key because it can accommodate over two billion positive integers.

• Because it allows for negative integer values which are essential for database indexing.

• A 4-byte integer is favored because it can represent over four billion values, more than sufficient for any reasonable dimension.

• The 4-byte integer is the standard for surrogate keys because it supports alphanumeric characters.

Which of the following is NOT identified as a fundamental concept that successful data warehousing depends on according to the Business Dimensional Lifecycle?

• Focus on the business and its specific needs.

• Dimensionally structure the data for straightforward access via ad hoc queries or reports

• Develop the data warehouse environment in a single, comprehensive rollout instead of manageable increments.

• Iteratively develop the data warehouse environment in manageable lifecycle increments.

What is the primary role of a data modeler in the dimensional modeling process?

• To act as a liaison between the technical team and the business users, translating business needs into technical specifications.

• To focus on the operational management of data, ensuring data quality and consistency across systems.

• To provide primary design responsibility and facilitate the creation and maintenance of the dimensional model.

• To oversee the governance of the data warehouse and ensure compliance with data policies and procedures.

Which of the following are key deliverables when designing a dimensional model?

• High-level model diagram

• Attribute and metrics list dimensional design worksheet

• Detailed

• All of the above