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Podcast
Questions and Answers
Which modeling approach is not supported by Flow.BI?
Which modeling approach is not supported by Flow.BI?
- Data-driven Data Vault
- Logical Data Vault (correct)
- Source Vault
- Hybrid Data Vault
What is a feature of the Data-driven Data Vault?
What is a feature of the Data-driven Data Vault?
- It relies on complex business logic.
- It models the raw data as it is utilized by the business. (correct)
- It is limited only to historical data.
- It models the business as it should be.
Which of the following is true regarding Flow.BI's supported modeling approaches?
Which of the following is true regarding Flow.BI's supported modeling approaches?
- Flow.BI supports modeling the business as it should be.
- Logical and Source Vault approaches are equally supported.
- Any approach based on business logic is acceptable.
- Only the Data-driven Data Vault approach is endorsed. (correct)
What does the Source Vault primarily focus on?
What does the Source Vault primarily focus on?
What does the data-driven approach emphasize?
What does the data-driven approach emphasize?
Flow.BI supports Logical Data Vault modeling.
Flow.BI supports Logical Data Vault modeling.
The Data-driven Data Vault approach exclusively models raw data as it is used by the business.
The Data-driven Data Vault approach exclusively models raw data as it is used by the business.
Only the Source Vault method is compatible with Flow.BI.
Only the Source Vault method is compatible with Flow.BI.
There are three major choices for Data Vault modeling.
There are three major choices for Data Vault modeling.
Implementing modeling approaches that rely on business logic is possible with Flow.BI.
Implementing modeling approaches that rely on business logic is possible with Flow.BI.
Match the Data Vault modeling approaches with their primary focus:
Match the Data Vault modeling approaches with their primary focus:
Match the following statements with their relevance to Flow.BI:
Match the following statements with their relevance to Flow.BI:
Match the following descriptions with the appropriate Data Vault modeling types:
Match the following descriptions with the appropriate Data Vault modeling types:
Match the following terms with their associated characteristics:
Match the following terms with their associated characteristics:
Match the terms with their definitions as they relate to Data Vault modeling:
Match the terms with their definitions as they relate to Data Vault modeling:
What is the primary focus of the data-driven Data Vault model?
What is the primary focus of the data-driven Data Vault model?
Why is the data-driven Data Vault considered a middle ground between other models?
Why is the data-driven Data Vault considered a middle ground between other models?
What limitation is associated with the Logical Data Vault model in relation to Flow.BI?
What limitation is associated with the Logical Data Vault model in relation to Flow.BI?
Which of the following describes an advantage of a data-driven Data Vault model?
Which of the following describes an advantage of a data-driven Data Vault model?
What performance issue is associated with using the Source Vault approach in Flow.BI?
What performance issue is associated with using the Source Vault approach in Flow.BI?
Which statement reflects the principles of the Data Vault model?
Which statement reflects the principles of the Data Vault model?
Why is the data-driven approach recommended over the Source Vault model?
Why is the data-driven approach recommended over the Source Vault model?
What characterizes the Source Vault modeling approach?
What characterizes the Source Vault modeling approach?
Which aspect makes the Data Vault model flexible and extensible?
Which aspect makes the Data Vault model flexible and extensible?
What must be avoided when implementing other modeling approaches in Flow.BI?
What must be avoided when implementing other modeling approaches in Flow.BI?
Flashcards
Data-Driven Data Vault
Data-Driven Data Vault
A data warehousing methodology that models data based on how it's used by the business, not how it should ideally be. It focuses on the actual data structures and relationships.
Logical Data Vault
Logical Data Vault
A data warehousing methodology that models the business as it should be, focusing on ideal data structures and relationships.
Source Vault
Source Vault
A data warehousing methodology that models raw data directly from sources, without applying any business logic or transformations.
Flow.BI Data Vault Support
Flow.BI Data Vault Support
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Flexibility with Other Data Vault Models
Flexibility with Other Data Vault Models
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Flow.BI's Data Vault Approach
Flow.BI's Data Vault Approach
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Flow.BI's Data Vault Restrictions
Flow.BI's Data Vault Restrictions
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Data-Driven Data Vault for Automation
Data-Driven Data Vault for Automation
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Flow.BI Source Vault Support
Flow.BI Source Vault Support
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Logical Data Vault Incompatibility
Logical Data Vault Incompatibility
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Study Notes
Data Vault Modelling Choices
- Flow.BI supports only the data-driven Data Vault model.
- Three main Data Vault modelling approaches exist:
- Logical Data Vault: Models the business as it should be, applying business logic.
- Source Vault: Models raw data only, ignoring any business rules.
- Data-driven Data Vault: Models raw data as it is used by the business, a middle ground approach.
- Flow.BI prioritizes the data-driven approach, as it's a model useful for future automation.
- A Logical Data Vault approach is not compatible with Flow.BI, due to its reliance on business logic.
- Flow.BI only supports the Data-driven Data Vault approach. Other Data Vault approaches (Source Vault) are possible but not recommended if not directly business logic driven.
- Implementing other approaches (Source Vault) is possible, if they do not depend on business logic.
- Implementing a Source Vault is possible within Flow.BI, but is not recommended due to potential performance issues.
- The data-driven approach is recommended for its flexibility, scalability and support for additional automation features.
Data-Driven Data Vault Model
- A data-driven Data Vault model is a flexible and scalable model, designed for data-driven organizations.
- Key principles include:
- Data is the source of truth: Raw data stored without transformations to allow varied uses (analytics, reporting, machine learning).
- Flexibility and Extensibility: Designed for organizational change.
- Scalability: Ability to handle large datasets.
- Typically implemented using relational databases, but can adapt to other database types like NoSQL, if desired.
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Description
This quiz explores the various approaches to Data Vault modelling, focusing on the data-driven model supported by Flow.BI. Learn about the distinctions between Logical Data Vault, Source Vault, and the data-driven approach, as well as their compatibility with business logic. Test your understanding of these methodologies and how they apply in the business context.
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