_______ is a schema design approach where data is intentionally duplicated or grouped together in ways that are not strictly necessary for normalization.
- Denormalization
- Horizontal Partitioning
- Normalization
- Vertical Partitioning
Denormalization is a schema design approach where data is intentionally duplicated or grouped together beyond the strict requirements of normalization. This is done to improve query performance and simplify data retrieval at the cost of redundancy.
Scenario: A financial institution's database experiences frequent deadlock issues, impacting transaction throughput and system reliability. How would you mitigate these issues and ensure optimal database performance?
- Implement optimistic concurrency control, enable database encryption, increase server RAM, and use a distributed cache
- Increase server clock speed, archive old data, implement database replication, and enable query rate limiting
- Optimize SQL queries, increase database isolation level, use proper indexing, and implement deadlock detection mechanisms
- Upgrade the database software, implement horizontal scaling, use distributed transactions, and optimize network bandwidth
Deadlock issues in a financial institution's database can be mitigated by optimizing SQL queries, increasing the database isolation level, using proper indexing, and implementing deadlock detection mechanisms. These measures ensure optimal performance and reliability in transaction processing.
What is the purpose of clustering in storage optimization?
- Enhancing data security
- Improving data locality and access speed
- Increasing database scalability
- Reducing network latency
Clustering in storage optimization aims to improve data locality and access speed. By organizing related data together, it reduces the need to fetch data from distant locations, thereby enhancing overall system performance. This is particularly beneficial in scenarios where data access speed is critical.
The process of __________ involves grouping data into logical entities based on their relationships and attributes.
- Aggregation
- Categorization
- Clustering
- Normalization
The process of normalization involves grouping data into logical entities based on their relationships and attributes. It is a crucial step in database design to eliminate redundancy and ensure data integrity.
ER diagram tools often provide templates for various database _______.
- Configurations
- Instances
- Models
- Schemas
ER diagram tools often provide templates for various database models. These templates serve as starting points for users, helping them save time and maintain consistency in designing databases based on established models and best practices.
Scenario: A healthcare organization needs to track patient demographics, medical procedures, and billing information for reporting purposes. How would you implement Dimensional Modeling in this scenario?
- Fact table for billing information, dimensions for patient demographics and medical procedures
- Fact table for medical procedures, dimensions for patient demographics and billing information
- Fact table for patient demographics, dimensions for medical procedures and billing information
- No need for Dimensional Modeling in healthcare scenarios
In this case, a Fact table for medical procedures with dimensions for patient demographics and billing information is appropriate. This allows for efficient analysis based on medical procedures, while also considering patient and billing details.
Scenario: A software development team is working on a new project. They need to design the database schema. Which data modeling language would you recommend they use, and why?
- ERD
- NoSQL
- SQL
- UML
For designing a database schema, the recommended data modeling language is ERD (Entity-Relationship Diagram). ERD provides a visual representation of the database structure, including entities, relationships, and attributes. It is specifically designed for database design and helps in organizing and understanding the relationships between different entities.
Reverse Engineering involves analyzing an existing database schema to create a _______ data model.
- Abstract
- Conceptual
- Concrete
- Logical
Reverse Engineering starts with a Conceptual Data Model. It involves analyzing an existing database schema to understand the business rules and requirements that led to its creation. This helps in creating a high-level representation of the data structure.
Scenario: A data modeling project requires the creation of multiple versions of the data model to explore different design options. Which aspect of version control facilitates this requirement?
- Branching
- Check-in/check-out
- Merging
- Tagging
Tagging is the aspect of version control that facilitates creating multiple versions of the data model to explore different design options. With tagging, specific points in the project's history are marked, allowing the team to refer back to or recreate a particular version if needed.
_______ is a Dimensional Modeling technique used to handle slowly changing dimensions.
- Conforming Dimension
- Degenerate Dimension
- Junk Dimension
- Slowly Changing Dimension
Slowly Changing Dimensions (SCD) is a Dimensional Modeling technique used to handle changes in dimension attributes over time. SCDs are categorized into different types (Type 1, Type 2, etc.) based on how they manage historical changes in data, ensuring accuracy in analytical reporting.