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DP-203 · Question #206

You have an Azure Synapse Analytics dedicated SQL pool. You need to Create a fact table named Table1 that will store sales data from the last three years. The solution must be optimized for the…

The correct answer is D. month. When designing a fact table in a data warehouse, it is important to consider the types of queries that will be run against it. In this case, the queries that need to be optimized include: show order counts by week, calculate sales totals by region, calculate sales totals by…

Submitted by lucia.co· Mar 30, 2026Design and implement data storage

Question

You have an Azure Synapse Analytics dedicated SQL pool. You need to Create a fact table named Table1 that will store sales data from the last three years. The solution must be optimized for the following query operations:

  • Show order counts by week.
  • Calculate sales totals by region.
  • Calculate sales totals by product.
  • Find all the orders from a given month.

Which data should you use to partition Table1?

Options

  • Aregion
  • Bproduct
  • Cweek
  • Dmonth

How the community answered

(26 responses)
  • A
    4% (1)
  • B
    12% (3)
  • C
    4% (1)
  • D
    81% (21)

Explanation

When designing a fact table in a data warehouse, it is important to consider the types of queries that will be run against it. In this case, the queries that need to be optimized include: show order counts by week, calculate sales totals by region, calculate sales totals by product, and find all the orders from a given month. Partitioning the table by month would be the best option in this scenario as it would allow for efficient querying of data by month, which is necessary for the query operations described above. For example, it would be easy to find all the orders from a given month by only searching the partition for that specific month.

Topics

#table partitioning#dedicated SQL pool#fact table design#query optimization

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