PROFESSIONAL-DATA-ENGINEER · Question #256
Your company is implementing a data warehouse using BigQuery, and you have been tasked with designing the data model. You move your on-premises sales data warehouse with a star data schema to BigQuery
The correct answer is D. Partition the data by transaction date. Explanation/Reference: Star schema is supported by Big Query but is not the most efficient form, if you should design a schema from scratch google recommend to use nested and repeated fields. In this case, you already have done a migration of the schema and data, so it sounds goo
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Options
- ADenormalize the data
- BShard the data by customer ID
- CMaterialize the dimensional data in views
- DPartition the data by transaction date
How the community answered
(20 responses)- A5% (1)
- B5% (1)
- C10% (2)
- D80% (16)
Explanation
Explanation/Reference: Star schema is supported by Big Query but is not the most efficient form, if you should design a schema from scratch google recommend to use nested and repeated fields. In this case, you already have done a migration of the schema and data, so it sounds good and with less effort to do partitioning by transaction date than to redesign the schema. And other aspect to consider is that this is a data warehouse, so is sure that there is an ETL process and if you change the schema you must adapt the ETL
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