In a Star Schema, the central table is the Fact Table. This table contains the core data of the schema and is usually surrounded by Dimension Tables that provide context and additional details for the data in the Fact Table. The Fact Table typically contains numerical measures or facts that business users want to analyze.

Indexing improves query performance by creating a quick access path to the data. It reduces the number of records that need to be scanned, making data retrieval faster for specific queries.

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.

The Check constraint in a database allows you to define a condition or expression that must be satisfied for the data to be considered valid. It is used to ensure that data adheres to specific criteria, providing data integrity at the column level.

NoSQL databases often rely on eventual consistency in distributed systems compared to traditional relational databases. Unlike traditional databases that emphasize strong consistency through distributed transactions and ACID properties, NoSQL databases prioritize low-latency operations and high availability, accepting temporary inconsistencies that will eventually be resolved.

In denormalization, the creation of Aggregate tables is a technique to store precomputed results. These tables contain summarized data, reducing the need for complex calculations during query execution and improving overall performance.