Which type of dimension change captures historical data without overwriting existing records?

  • Type 1
  • Type 2
  • Type 3
  • Type 4
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.

_______ is the process of physically grouping related data together to improve query performance and reduce disk I/O.

  • Data Clustering
  • Data Encryption
  • Data Serialization
  • Data Validation
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.

_______ techniques in Dimensional Modeling aim to improve query performance by pre-calculating and storing aggregated data.

  • Aggregation
  • Indexing
  • Normalization
  • Partitioning
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.

What factors should be considered when choosing the appropriate Slowly Changing Dimensions (SCD) technique for a data warehouse?

  • Availability of primary keys
  • Database normalization level
  • Number of tables in the database
  • Volume of data changes, Query performance, and Data storage requirements
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.

What is a key characteristic of document databases in terms of schema flexibility?

  • Dynamic schema
  • Fixed schema
  • Relational schema
  • Semi-structured schema
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.

Scenario: A company has employees and projects. An employee can work on multiple projects, and a project can have multiple employees working on it. Which type of relationship would you use to represent this scenario in an ERD?

  • Many-to-Many
  • Many-to-One
  • One-to-Many
  • One-to-One
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, an _______ key is a key that consists of more than one attribute.

  • Composite
  • Foreign
  • Primary
  • Unique
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.

One technique used in denormalization is the creation of _______ tables to store precomputed results.

  • Aggregate
  • Lookup
  • Metadata
  • Staging
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.

What is the purpose of Slowly Changing Dimensions (SCD) in data modeling?

  • To capture changes to dimension data over time
  • To design complex queries
  • To enforce data integrity constraints
  • To speed up data retrieval from databases
Slowly Changing Dimensions (SCD) in data modeling are used to capture changes to dimension data over time. They allow for the tracking of historical data and help maintain a history of changes to dimensional attributes, which is crucial for analysis and reporting purposes.

What does "Forward Engineering" refer to in the context of database design?

  • Creating a conceptual data model
  • Generating a database schema from a higher-level model
  • Modifying an existing database schema
  • Optimizing a database for performance
In database design, "Forward Engineering" involves generating a database schema from a higher-level model, such as a conceptual data model. This process moves from an abstract representation to a concrete implementation, helping in the actual creation of the database structure.