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Podcast
Questions and Answers
Which component generates the (logical) model for the Raw Data Vault?
Which component generates the (logical) model for the Raw Data Vault?
- Staging
- Definitions
- Flow.BI (correct)
- Source metadata
Where is staging performed for the Raw Data Vault?
Where is staging performed for the Raw Data Vault?
- Flow.BI
- Definitions
- Source metadata
- Staging (correct)
What is used to perform staging in the Raw Data Vault?
What is used to perform staging in the Raw Data Vault?
- Staging
- Source metadata (correct)
- Flow.BI
- Definitions
True or false: Data Vault 2.0 Reference Architecture Flow.BI generates the physical model for the Raw Data Vault.
True or false: Data Vault 2.0 Reference Architecture Flow.BI generates the physical model for the Raw Data Vault.
True or false: Staging in the Raw Data Vault is performed using source metadata and definitions from the logical Raw Data Vault.
True or false: Staging in the Raw Data Vault is performed using source metadata and definitions from the logical Raw Data Vault.
True or false: Flow.BI generates the logical model for the Raw Data Vault.
True or false: Flow.BI generates the logical model for the Raw Data Vault.
Match the following components with their roles in Data Vault 2.0 Reference Architecture:
Match the following components with their roles in Data Vault 2.0 Reference Architecture:
Match the following terms with their definitions in Data Vault 2.0 Reference Architecture:
Match the following terms with their definitions in Data Vault 2.0 Reference Architecture:
Match the following roles with their associated tasks in Data Vault 2.0 Reference Architecture:
Match the following roles with their associated tasks in Data Vault 2.0 Reference Architecture:
Match the following layers with their descriptions in the Data Vault 2.0 reference architecture:
Match the following layers with their descriptions in the Data Vault 2.0 reference architecture:
Match the following layers with the tasks they perform in the Data Vault 2.0 reference architecture:
Match the following layers with the tasks they perform in the Data Vault 2.0 reference architecture:
Match the following layers with their associated models in the Data Vault 2.0 reference architecture:
Match the following layers with their associated models in the Data Vault 2.0 reference architecture:
Match the following terms with their definitions in the Data Vault 2.0 reference architecture:
Match the following terms with their definitions in the Data Vault 2.0 reference architecture:
Match the following layers with their primary purposes in the Data Vault 2.0 reference architecture:
Match the following layers with their primary purposes in the Data Vault 2.0 reference architecture:
Match the following layers with their potential additions to the Data Vault 2.0 reference architecture:
Match the following layers with their potential additions to the Data Vault 2.0 reference architecture:
Match the following layers with their usage in the Data Vault 2.0 reference architecture:
Match the following layers with their usage in the Data Vault 2.0 reference architecture:
Match the following layers with their potential modifications in the Data Vault 2.0 reference architecture:
Match the following layers with their potential modifications in the Data Vault 2.0 reference architecture:
Match the following layers with their potential additions in the Data Vault 2.0 reference architecture:
Match the following layers with their potential additions in the Data Vault 2.0 reference architecture:
Which layer of the Data Vault 2.0 reference architecture is used to clean and transform data before it is loaded into the Data Vault?
Which layer of the Data Vault 2.0 reference architecture is used to clean and transform data before it is loaded into the Data Vault?
What is the core layer of the Data Vault that stores the historical data from the source systems?
What is the core layer of the Data Vault that stores the historical data from the source systems?
Which layer in the Data Vault 2.0 reference architecture is used to attach the results of the business logic and often includes the business logic itself?
Which layer in the Data Vault 2.0 reference architecture is used to attach the results of the business logic and often includes the business logic itself?
Which layer in the Data Vault 2.0 reference architecture provides access to the data for reporting and analytics?
Which layer in the Data Vault 2.0 reference architecture provides access to the data for reporting and analytics?
What is a potential addition to the Data Vault 2.0 reference architecture that organizations may choose to include?
What is a potential addition to the Data Vault 2.0 reference architecture that organizations may choose to include?
Which layer in the Data Vault 2.0 reference architecture is used to store data temporarily before it is loaded into the Data Vault?
Which layer in the Data Vault 2.0 reference architecture is used to store data temporarily before it is loaded into the Data Vault?
What is the purpose of the Raw Data Vault layer in the Data Vault 2.0 reference architecture?
What is the purpose of the Raw Data Vault layer in the Data Vault 2.0 reference architecture?
What is the primary purpose of the Business Vault layer in the Data Vault 2.0 reference architecture?
What is the primary purpose of the Business Vault layer in the Data Vault 2.0 reference architecture?
Which layer in the Data Vault 2.0 reference architecture is used for reporting and analytics?
Which layer in the Data Vault 2.0 reference architecture is used for reporting and analytics?
The Data Vault 2.0 reference architecture consists of four layers: staging, raw data vault, business vault, and information delivery.
The Data Vault 2.0 reference architecture consists of four layers: staging, raw data vault, business vault, and information delivery.
The staging layer is used to store historical data from the source systems.
The staging layer is used to store historical data from the source systems.
The raw data vault layer is where data is cleaned and transformed before being loaded into the data vault.
The raw data vault layer is where data is cleaned and transformed before being loaded into the data vault.
The business vault layer attaches the results of the business logic and often includes the business logic itself.
The business vault layer attaches the results of the business logic and often includes the business logic itself.
The information delivery layer in the Data Vault 2.0 reference architecture typically consists of star schemas, cubes, and data marts.
The information delivery layer in the Data Vault 2.0 reference architecture typically consists of star schemas, cubes, and data marts.
The Data Vault 2.0 reference architecture can be easily modified to meet the specific needs of an organization.
The Data Vault 2.0 reference architecture can be easily modified to meet the specific needs of an organization.
A data lake layer is a potential addition that organizations may choose to include in the Data Vault 2.0 reference architecture.
A data lake layer is a potential addition that organizations may choose to include in the Data Vault 2.0 reference architecture.
The staging layer is used to generate the logical model for the raw data vault.
The staging layer is used to generate the logical model for the raw data vault.
The raw data vault layer is the core layer that stores the historical data from the source systems.
The raw data vault layer is the core layer that stores the historical data from the source systems.
Study Notes
Data Vault 2.0 Reference Architecture
- Flow.BI generates the logical model for the Raw Data Vault, which is used as a basis for staging, using source metadata and definitions.
Layers of the Data Vault 2.0 Architecture
- Staging layer: temporary storage for data before loading into the Data Vault, used for cleaning, transforming, and creating reference tables.
- Raw Data Vault layer: core of the Data Vault, stores historical data from source systems, modeled using the Data Vault 2.0 data model.
- Business Vault layer: attaches business logic results, often including the business logic itself (in SQL views).
- Information delivery layer: provides access to Data Vault data for reporting and analytics, typically consists of star schemas, cubes, and data marts.
Flexibility and Adaptability
- The Data Vault 2.0 reference architecture is flexible and can be adapted to meet organization-specific needs.
- Additional layers can be added to the architecture, such as a data lake layer or a machine learning layer.
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Description
Learn about the different layers of the Data Vault 2.0 reference architecture, including the staging layer for temporary storage and data transformation, and the Raw Data Vault layer for storing historical data from source systems.
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