Tell about approaches to building DWH: Data Vault 2.0 vs snowflake/star — main entities, advantages, and disadvantages.

Data Vault 2.0 is a methodology for building data warehouses focused on flexibility, scalability, and historization. Main entities:

• Hubs — key business objects with unique business keys.
• Links — relationships between hubs, reflecting associations.
• Satellites — attributes and historical data related to hubs or links.

Advantages of Data Vault 2.0:

• High adaptability to business changes.
• Good support for historization and auditing.
• Separation of structure into keys, links, and attributes simplifies data loading and integration.

Disadvantages:

• More complex architecture and greater data redundancy.
• Requires more complex ETL logic.

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Snowflake and Star are classic data modeling schemas for DWH.

• Star: a central fact table is directly connected to dimension tables.
• Snowflake: dimensions are normalized, split into several related tables.

Advantages:

• Simplicity of understanding and query building (especially star).
• Good performance for analytical queries.
• Less data redundancy (especially snowflake).

Disadvantages:

• Less flexibility with changes in business logic.
• Difficulties with historization and auditing without additional mechanisms.

Summary: Data Vault 2.0 is suitable for complex, rapidly changing systems requiring auditing and historization, while snowflake/star are suited for traditional analytical DWH with a fixed model and simple queries.