ER diagram tools like Lucidchart and Draw.io are specifically designed for creating and visualizing Entity-Relationship Diagrams (ERDs). These tools provide a user-friendly interface to design and represent the structure of a database, including entities, attributes, and relationships.

Forward Engineering involves transforming a conceptual data model into a database schema, essentially creating the database structure from an abstract representation. In contrast, Reverse Engineering transforms an existing database schema back into a conceptual data model, providing insight into the database's structure.

In class-table inheritance, each subclass is represented by a separate table. This design approach allows for a clear distinction between the attributes specific to each subclass while maintaining a connection to the superclass.

The GROUP BY clause in SQL is used to group rows based on the values in one or more columns. It is often used in conjunction with aggregate functions to perform operations on each group separately, providing a way to analyze and summarize data.

MySQL Workbench primarily offers graphical features for database design and management. Users can visually design, model, and manage databases, allowing for an intuitive and user-friendly approach to database development.

Challenges in Reverse Engineering include the potential loss of information, ambiguity in relationships, and inconsistencies in data types. Inferring a conceptual data model from an existing schema can be complex due to these factors, requiring careful analysis and interpretation.

The notation (1,*) represents a Zero-to-Many cardinality, indicating that one entity must be present, but there can be many occurrences in the related entity. This is commonly used to represent optional relationships.

A key feature of ER diagram tools for beginners is a user-friendly drag-and-drop interface. This simplifies the process of designing ERDs by allowing users to easily add entities, attributes, and relationships to the diagram without the need for complex coding or scripting.

Implementing compression techniques in database systems poses challenges such as increased computational overhead. While compression reduces storage requirements, the process of compressing and decompressing data can be resource-intensive, impacting system performance. It's crucial to balance the benefits of compression with its computational costs.

Forward Engineering involves the generation of SQL scripts to create a database schema based on a conceptual model. This process translates the high-level design into a working database with tables, relationships, and constraints. SQL is commonly used for this purpose.