Data Vault on BigQuery


In this workshop you will not only master BigQuery, but also learn that unlike traditional data modeling techniques, Data Vault model is highly scalable and can adapt easily to ever changing business requirements. During the course we simulate a real-world end-to-end scenario – processing metrics generated by devices that capture usage in real-time. The technology that we will use is BigQuery. All exercises will be done within BigQuery UI on Google Cloud Platform.


   Target Audience

Data Analysts, Analytics Engineers & Data Engineers, who are interested in learning BigQuery and modern modeling methods.


    Requirements (what you should know to attend fully):

  • SQL familiarity: DQL, DDL, DML.
  • Basic understanding of ETL, ELT processes.
  • Beginners experience with command-line.
  • Laptop with internet access.


    Participant’s ROI (what you will take away):

  • Concise and practical knowledge of applying Data Vault to solve business problems.
  • Hands-on coding experience under supervision of experienced BigQuery engineers.
  • Tips about real world applications and best practices.


    Training Materials

All participants will get training materials in the form of PDF files containing slides with theory and exercise manual with the detailed description of all the tasks.


    Time Box

2,5 hours



Part #1 - Introduction to Big Query

  • Key concepts
  • Basic data processing in BigQuery
  • Hands-on exercises

Part #2 - Introduction to Data Vault and the use case

  • High level introduction to Data Vault
  • Business problem definition
  • Exported data overview
  • Hands-on exercises (pen & paper)

Part #3 - Modeling Raw layer

  • Modeling RAW layer in BigQuery
  • Loading Hubs
  • Loading Satellites

Part #4 - Modeling InfoMarts

  • Business problem definition
  • Star schema design
  • Answering business problems (solving business problems or answering questions)

Part #5 - Troubleshooting

  • Intro to BigQuery troubleshooting
  • Optimizing BigQuery (partitioning, clustering, materialized views)
  • Optimizing Data Vault model
  • Hands-on exercises

Part #6  - Summary


Keywords: Data Warehouse, Data Analytics, DV, Data Vault, SQL, BigQuery, Data Modeling


    Session leader:



Evention sp. z o.o

Rondo ONZ 1 Str,

Warsaw, Poland


Weronika Warpas

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