Functional data partitioning divides data based on specific criteria or functions relevant to the application. This approach allows for tailored partitioning strategies that align with the application's logic, facilitating optimized data distribution and retrieval.

A Data Warehouse integrates data from multiple sources. This includes data from different departments, systems, and formats to provide a unified view for analytical purposes. The integration helps in obtaining a comprehensive and consistent view of the organization's data.

The key difference is that a primary key cannot have null values, ensuring each record is uniquely identified, while a unique key can have null values, allowing for some flexibility in data constraints.

A Document Store is well-suited for a recommendation engine in a streaming service. It allows storing and retrieving complex user data, such as viewing histories and preferences, in a flexible and scalable manner, enabling efficient analysis for personalized recommendations.

In a star schema, the relationship between fact and dimension tables is one-to-many. This means that for each record in the fact table (containing transactional data), there can be multiple related records in the dimension tables (containing descriptive attributes). This structure enables efficient querying and analysis of data in a data warehouse environment.

Aggregation improves query performance by reducing the amount of data processed. Instead of working with detailed records, aggregating data allows databases to handle summary values, which is more efficient for queries. This optimization becomes crucial, especially in large databases with extensive datasets.

All of the options are essential steps in performing effective Reverse Engineering. Analyzing existing data, documenting the structure, and interviewing knowledgeable personnel help in understanding and reconstructing the database schema.

Data Encryption is not a compression technique. While encryption is essential for securing data, it focuses on converting data into a secure format rather than reducing its size. Common compression techniques like Run-Length Encoding, Huffman Coding, and Lempel-Ziv-Welch aim to minimize data size for storage or transmission purposes.

A NoSQL database is a type of document-based database optimized for high-speed data retrieval and processing. NoSQL databases are non-relational and provide flexible schema designs, making them suitable for handling unstructured and semi-structured data efficiently.

The key distinction lies in the presence of a primary key. A strong entity always has a primary key, while a weak entity relies on a partial key and requires the association with a strong entity for identity. Weak entities lack independence and rely on a strong entity for survival.

ER diagram tools facilitate team collaboration by providing role-based access to different team members. This ensures that each team member has the appropriate level of access and control, promoting effective collaboration in large-scale database projects.

One of the key features of column-family stores is their ability to handle mixed (read/write) workloads efficiently. This makes them suitable for applications with diverse and dynamic usage patterns, such as those in the realm of big data analytics and real-time data processing.