Which property of graph databases makes them particularly suitable for recommendation systems and social networks?
- Ability to store large volumes of structured data
- Native representation of relationships
- Support for ACID transactions
- Use of SQL as the query language
Graph databases are particularly suitable for recommendation systems and social networks due to their native representation of relationships. In a graph database, relationships are first-class citizens, making it efficient to traverse and analyze connections between entities, a key requirement in recommendation systems and social networks.
In Slowly Changing Dimensions (SCD), how does Type 4 handle historical data?
- Adds new rows for each change
- Creates separate tables for historical data
- Overwrites existing historical records
- Uses effective dating or versioning
Type 4 SCD handles historical data by using effective dating or versioning. Instead of adding new rows, it maintains the original row with an effective date or version number, allowing for a more compact representation of historical changes without cluttering the table with additional rows.
A social media platform needs to store a vast amount of multimedia content, including images and videos. Discuss the considerations they should take into account when implementing compression techniques for this data.
- Adaptive Compression
- Image Compression
- Lossy Compression
- Video Compression
Considering the large volume of multimedia content, a social media platform should consider Lossy Compression. This method sacrifices some data to achieve higher compression ratios, making it suitable for non-critical content like images and videos where a slight loss in quality is acceptable for significant storage savings.
What does "CAP theorem" stand for in the context of NoSQL databases?
- Centralized Architecture Paradigm
- Common Access Protocol theorem
- Concurrent Access Principle theorem
- Consistency, Availability, Partition Tolerance
CAP theorem states that in a distributed system, it's impossible to achieve all three of Consistency, Availability, and Partition Tolerance simultaneously. Understanding CAP helps in making informed decisions when designing and selecting NoSQL databases for specific use cases.
A _______ dimension table in a Star Schema contains reference attributes.
- Conformed
- Degenerate
- Fact
- Slowly Changing
In a Star Schema, a Conformed dimension table contains reference attributes that are consistent and shared across multiple fact tables. This allows for uniformity in reporting and analysis, as the same dimension can be used across different parts of the data warehouse.
What are some common challenges faced during conceptual schema design?
- Ambiguous requirements
- Indexing complexities
- Query optimization issues
- Schema normalization challenges
Common challenges in conceptual schema design include dealing with ambiguous requirements, where clarity is lacking. Clearing up ambiguities is crucial to ensure the final schema accurately reflects business needs.
Explain the concept of a multivalued attribute in database modeling.
- An attribute that can have multiple values for each entity
- An attribute that is derived from another attribute
- An attribute that is not essential for an entity
- An attribute with a single value for each entity
A multivalued attribute in database modeling is an attribute that can have multiple values for each entity. This concept is used to represent situations where an entity can have multiple values for a specific attribute, without creating a separate entity for each value.
Database _______ involves fine-tuning the physical design and configuration parameters to optimize performance.
- Clustering
- Optimization
- Scaling
- Tuning
Database tuning involves adjusting the physical design and configuration parameters of a database to optimize its performance. This includes optimizing queries, indexing, and other settings to ensure efficient data retrieval and processing. Tuning is an ongoing process to adapt the database to changing requirements and workload.
A Data Mart typically focuses on a specific _______ area.
- Chronological
- Functional
- Geographic
- Organizational
A Data Mart typically focuses on a specific functional area. Unlike a Data Warehouse, which covers the entire organization, a Data Mart is designed for a particular business unit or department's specific needs, providing more targeted insights.
What is the difference between horizontal and vertical data partitioning?
- Horizontal partitioning divides a table into columns based on a condition, while vertical partitioning divides a table into rows
- Horizontal partitioning divides a table into rows based on a condition, while vertical partitioning divides a table into columns
- Horizontal partitioning is suitable for OLAP systems, while vertical partitioning is suitable for OLTP systems
- Horizontal partitioning is used for range-based data, while vertical partitioning is used for hash-based data
Horizontal data partitioning involves dividing a table into rows based on a condition, allowing for efficient storage and retrieval of specific subsets of data. Vertical partitioning, on the other hand, involves dividing a table into columns, typically based on the frequency of access, reducing I/O overhead.