Data warehouse vault

  • How does Data Vault work?

    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..

  • What is a vault in database?

    Database Vault is a security option for Oracle Database Enterprise Edition.
    It makes it possible to protect sensitive data with higher security rules than usual.
    Normally, a database administrator with the DBA role has access to all data in the Oracle database..

  • What is data vault in data warehouse?

    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..

  • Which is a benefit of data vault?

    One of the main benefits of data vault is that it can handle complex and changing data sources, such as operational systems, streaming data, or external data.
    Data vault can capture the history and lineage of data, as well as the changes and variations in data structures and semantics over time..

  • Why is Data Vault important?

    The Data Vault essentially defines the Ontology of an Enterprise in that it describes the business domain and relationships within it.
    Processing business rules must occur before populating a Star Schema.
    With a Data Vault you can push them downstream, post EDW ingestion..

  • 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.
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.
A data vault is a data modeling design pattern used to build a data warehouse for enterprise-scale analytics.

What is a data vault?

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

Why is a data vault suited to the Lakehouse methodology?

A Data Vault is well suited to the lakehouse methodology since the data model is easily extensible and granular with its hub, link and satellite design so design and ETL changes are easily implemented

Let's understand a few building blocks for a Data Vault

In general, a Data Vault model has three types of entities:

Why should you use a data vault model in Databricks Lakehouse?

The robust and scalable Delta Lake storage format enables customers to build a raw vault where unmodified data is stored, and a business vault where business rules and transformation are applied if required

Both will align to the design earlier hence get the benefits of a Data Vault Model

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Implementing a Data Vault Model in Databricks Lakehouse

A data vault is a data modeling design pattern used to build a data warehouse for enterprise-scale analytics

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