Lossless compression reduces the storage size of data without losing any information. It is commonly used when it's important to preserve all the original data, such as in databases or text files. Unlike lossy compression, there is no loss of quality in the compressed data.

In a fact table, each record represents a transaction at a specific level of detail. A fact table contains quantitative data, such as measurements or metrics, and is typically associated with a timestamp to capture when the transaction occurred. This helps in analyzing and understanding the details of specific events or transactions in the dataset.

In this scenario, the best approach is to use a superclass-subclass relationship. By having a staff superclass and professor/administrative staff subclasses, you can inherit common attributes from the superclass while allowing specific attributes for each subclass. This promotes data integrity and reduces redundancy.

Vertical partitioning involves splitting tables based on columns, which means dividing a table into smaller, more manageable parts based on specific columns. This can be beneficial for improving query performance and managing data more efficiently.

A composite key consists of multiple columns to uniquely identify a record, whereas a single-column key uses only one column for this purpose. Composite keys are often used when a single column cannot guarantee uniqueness.

DDL stands for Data Definition Language in SQL. It is used to define the structure of the database, including creating, altering, and dropping tables and defining constraints. DDL statements include CREATE, ALTER, DROP, and TRUNCATE. Understanding DDL is crucial for database schema design and management.

Clustering in a distributed database system offers advantages such as increased data locality, which means related data is stored together, reducing network overhead. It also enhances fault tolerance as data redundancy is increased. This improves system resilience and reliability.

Relationships in an ERD are represented by a diamond shape. This symbolizes the connection between entities, indicating how data is associated and shared between them.

Advanced ER diagram tools often provide validation functionality to ensure data consistency. This involves checking the diagram against predefined rules and constraints, helping users identify errors or inconsistencies in their data model. Validation is crucial for maintaining the integrity of the database design.

Using a column-family store over a relational database provides advantages like improved scalability for read-heavy workloads. Column-family stores are designed to efficiently handle large amounts of data with high read-throughput, making them suitable for applications with demanding query patterns and analytical workloads.