[03/Mersey/01]

[03/Mersey/01]

Created by
@MultiPurposeMalachite

Questions and Answers

Which component generates the (logical) model for the Raw Data Vault?

Flow.BI

Where is staging performed for the Raw Data Vault?

Staging

What is used to perform staging in the Raw Data Vault?

Source metadata

True or false: Data Vault 2.0 Reference Architecture Flow.BI generates the physical model for the Raw Data Vault.

<p>False</p> Signup and view all the answers

True or false: Staging in the Raw Data Vault is performed using source metadata and definitions from the logical Raw Data Vault.

<p>True</p> Signup and view all the answers

True or false: Flow.BI generates the logical model for the Raw Data Vault.

<p>True</p> Signup and view all the answers

Match the following components with their roles in Data Vault 2.0 Reference Architecture:

<p>Flow.BI = Generates the (logical) model for the Raw Data Vault Staging = Performed using source metadata and definitions from the logical Raw Data Vault Raw Data Vault = Location where Flow.BI generates the (logical) model Physical Model = Not generated by Flow.BI in Data Vault 2.0 Reference Architecture</p> Signup and view all the answers

Match the following terms with their definitions in Data Vault 2.0 Reference Architecture:

<p>Raw Data Vault = Location where staging is performed using source metadata and definitions Staging = Process performed using source metadata and definitions from the logical Raw Data Vault Flow.BI = Component that generates the (logical) model for the Raw Data Vault Physical Model = Not generated by Flow.BI in this architecture</p> Signup and view all the answers

Match the following roles with their associated tasks in Data Vault 2.0 Reference Architecture:

<p>Flow.BI = Generates the (logical) model for the Raw Data Vault Staging = Performed using source metadata and definitions from the logical Raw Data Vault Raw Data Vault = Location where Flow.BI generates the (logical) model Physical Model = Not generated by Flow.BI in this architecture</p> Signup and view all the answers

Match the following layers with their descriptions in the Data Vault 2.0 reference architecture:

<p>Staging layer = Temporary layer where data is stored before it is loaded into the Data Vault Raw Data Vault layer = Core of the Data Vault that stores the historical data from the source systems Business Vault layer = Layer used to attach the results of the business logic Information delivery layer = Provides access to the data in the Data Vault for reporting and analytics</p> Signup and view all the answers

Match the following layers with the tasks they perform in the Data Vault 2.0 reference architecture:

<p>Staging layer = Used to clean and transform the data, and to create the reference tables Raw Data Vault layer = Stores the historical data from the source systems Business Vault layer = Attaches the results of the business logic, often along with the business logic itself Information delivery layer = Provides access to the data in the Data Vault for reporting and analytics</p> Signup and view all the answers

Match the following layers with their associated models in the Data Vault 2.0 reference architecture:

<p>Staging layer = No specific model mentioned in the text Raw Data Vault layer = Modeled using the Data Vault 2.0 data model Business Vault layer = No specific model mentioned in the text Information delivery layer = Typically consists of star schemas, cubes, and data marts</p> Signup and view all the answers

Match the following terms with their definitions in the Data Vault 2.0 reference architecture:

<p>Data Vault 2.0 reference architecture = Layered architecture that consists of staging, raw data vault, business vault, and information delivery layers Staging layer = Temporary layer where data is stored before it is loaded into the Data Vault Raw Data Vault layer = Core of the Data Vault that stores the historical data from the source systems Business Vault layer = Layer used to attach the results of the business logic</p> Signup and view all the answers

Match the following layers with their primary purposes in the Data Vault 2.0 reference architecture:

<p>Staging layer = Clean and transform the data, and create the reference tables Raw Data Vault layer = Store the historical data from the source systems Business Vault layer = Attach the results of the business logic Information delivery layer = Provide access to the data for reporting and analytics</p> Signup and view all the answers

Match the following layers with their potential additions to the Data Vault 2.0 reference architecture:

<p>Staging layer = No specific additions mentioned in the text Raw Data Vault layer = No specific additions mentioned in the text Business Vault layer = No specific additions mentioned in the text Information delivery layer = No specific additions mentioned in the text</p> Signup and view all the answers

Match the following layers with their usage in the Data Vault 2.0 reference architecture:

<p>Staging layer = Used to store data before it is loaded into the Data Vault Raw Data Vault layer = Used to store the historical data from the source systems Business Vault layer = Used to attach the results of the business logic Information delivery layer = Used to provide access to the data for reporting and analytics</p> Signup and view all the answers

Match the following layers with their potential modifications in the Data Vault 2.0 reference architecture:

<p>Staging layer = Can be used to clean and transform the data, and to create the reference tables Raw Data Vault layer = Can be modeled using the Data Vault 2.0 data model Business Vault layer = No specific modifications mentioned in the text Information delivery layer = No specific modifications mentioned in the text</p> Signup and view all the answers

Match the following layers with their potential additions in the Data Vault 2.0 reference architecture:

<p>Staging layer = Additional layers like a data lake layer or a machine learning layer Raw Data Vault layer = No specific additions mentioned in the text Business Vault layer = No specific additions mentioned in the text Information delivery layer = No specific additions mentioned in the text</p> Signup and view all the answers

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?

<p>Staging layer</p> Signup and view all the answers

What is the core layer of the Data Vault that stores the historical data from the source systems?

<p>Raw Data Vault layer</p> Signup and view all the answers

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?

<p>Business Vault layer</p> Signup and view all the answers

Which layer in the Data Vault 2.0 reference architecture provides access to the data for reporting and analytics?

<p>Information delivery layer</p> Signup and view all the answers

What is a potential addition to the Data Vault 2.0 reference architecture that organizations may choose to include?

<p>Both A and B</p> Signup and view all the answers

Which layer in the Data Vault 2.0 reference architecture is used to store data temporarily before it is loaded into the Data Vault?

<p>Staging layer</p> Signup and view all the answers

What is the purpose of the Raw Data Vault layer in the Data Vault 2.0 reference architecture?

<p>To store historical data from source systems</p> Signup and view all the answers

What is the primary purpose of the Business Vault layer in the Data Vault 2.0 reference architecture?

<p>To attach the results of the business logic</p> Signup and view all the answers

Which layer in the Data Vault 2.0 reference architecture is used for reporting and analytics?

<p>Information delivery layer</p> Signup and view all the answers

The Data Vault 2.0 reference architecture consists of four layers: staging, raw data vault, business vault, and information delivery.

<p>True</p> Signup and view all the answers

The staging layer is used to store historical data from the source systems.

<p>False</p> Signup and view all the answers

The raw data vault layer is where data is cleaned and transformed before being loaded into the data vault.

<p>False</p> Signup and view all the answers

The business vault layer attaches the results of the business logic and often includes the business logic itself.

<p>True</p> Signup and view all the answers

The information delivery layer in the Data Vault 2.0 reference architecture typically consists of star schemas, cubes, and data marts.

<p>True</p> Signup and view all the answers

The Data Vault 2.0 reference architecture can be easily modified to meet the specific needs of an organization.

<p>True</p> Signup and view all the answers

A data lake layer is a potential addition that organizations may choose to include in the Data Vault 2.0 reference architecture.

<p>True</p> Signup and view all the answers

The staging layer is used to generate the logical model for the raw data vault.

<p>False</p> Signup and view all the answers

The raw data vault layer is the core layer that stores the historical data from the source systems.

<p>True</p> Signup and view all the answers

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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