Data warehouse data vault model
Is Data Vault a star schema?
The data vault architecture is meant to be complementary to the star schema methodology of modeling your data warehouse.
It acts as an additional layer between your staging and reporting layers.
- NF and star schema are great stand-alone architectures, but both have their pros and cons
What are the types of Data Vault?
The Data Vault consists of three basic entity types: hubs, links, and satellites.
The hub separates the business keys from the rest of the model, the link stores associations between hubs (business keys), and the satellite store the attributes of the hub or the link.Jul 15, 2023.
What is Data Vault in data warehouse?
A data vault is a relatively new design methodology for data warehouses.
Data vaults store raw data as-is without applying business rules.
Data transformation happens on-demand, and the results are available for viewing in a department-specific data mart..
What is the Data Vault model approach?
The data vault modeling is a hybrid approach based on third normal form and dimensional modeling aimed at the logical enterprise data warehouse.
The data vault model is built as a ground-up, incremental, and modular models that can be applied to big data, structured, and unstructured data sets..
What is the data vault modeling process?
The data vault modeling is a hybrid approach based on third normal form and dimensional modeling aimed at the logical enterprise data warehouse.
The data vault model is built as a ground-up, incremental, and modular models that can be applied to big data, structured, and unstructured data sets..
- Data vaults store raw data as-is without applying business rules.
Data transformation happens on-demand, and the results are available for viewing in a department-specific data mart.
While a traditional data warehouse structure relies on extensive data pre-processing, the data vault model takes a more agile approach. - The data vault architecture is meant to be complementary to the star schema methodology of modeling your data warehouse.
It acts as an additional layer between your staging and reporting layers.- NF and star schema are great stand-alone architectures, but both have their pros and cons
A data vault is a data modeling design pattern used to build a data warehouse for enterprise-scale analytics. The data vault has three types of entities: hubs, links, and satellites.
In Data Vault modelling, Satellites connect to Hubs or Links. They are Point in Time: so we can ask and answer the question, “what did we know when?” Satellites contain data about their parent Hub or Link and metadata about when the data was loaded, from where, and a business effectivity date.
Data Vault in Lakehouse
The Databricks Lakehouse Platform supports Data Vault Model very well Implementing A Data Vault Model in Databricks Lakehouse
Based on the design in the previous section, loading the hubs, satellites and links tables are straightforward Conclusion
In this blog, we learned about core Data Vault modeling concepts, and how to implement them using Delta Live Tables A data vault is a data modeling design pattern used to build a data warehouse for enterprise-scale analytics. The data vault has three types of entities: hubs, links, and satellites. Hubs represent core business concepts, links represent relationships between hubs, and satellites store information about hubs and relationships between them.
