In normalization, a transitive dependency occurs when a non-prime attribute determines another non-prime attribute. It violates the principles of normalization, and resolving such dependencies is crucial for achieving higher normal forms.

Type 2 dimension change captures historical data without overwriting existing records. It adds new records for each change, including a surrogate key and an effective date range, allowing for historical analysis while preserving the original data.

Data Clustering involves physically grouping related data together in storage. This process helps improve query performance by reducing the need for extensive disk I/O operations when retrieving related data. It enhances the efficiency of data retrieval operations, especially in scenarios where related data is commonly accessed together.

Aggregation techniques in Dimensional Modeling involve pre-calculating and storing aggregated data to enhance query performance. This reduces the need for complex computations during queries, making analytical processing faster and more efficient in data warehouses.

Choosing the appropriate SCD technique involves considering factors such as the volume of data changes, query performance, and data storage requirements. Each type of SCD has its strengths and weaknesses, and the decision should align with the specific needs and characteristics of the data warehouse environment.

A key characteristic of document databases is their dynamic schema. Unlike traditional relational databases with fixed schemas, document databases allow for flexible schema designs where each document can have its own unique structure. This flexibility accommodates evolving data requirements and simplifies the development process.

In this scenario, a Many-to-Many relationship is appropriate. This allows each employee to work on multiple projects, and each project to have multiple employees associated with it. It involves a junction table to manage the relationship.

In an ERD, a composite key is a key that consists of more than one attribute. It is used to uniquely identify an entity when a single attribute is not sufficient. Composite keys are common in situations where a combination of attributes is needed for uniqueness.

Aggregation in data modeling involves summarizing and combining data at a higher level. It is used to provide insights into the overall trends and patterns within a dataset, often involving the use of aggregation functions like SUM, AVG, COUNT, etc., to analyze and present data in a more meaningful way.

Strategies like the Two-phase commit protocol can be employed to ensure data consistency across partitions in distributed databases. This involves a coordinated approach to commit or abort transactions across all nodes, ensuring that data remains consistent even in a distributed environment.