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70-465 · Question #9

Drag and Drop Question You have a SQL Azure database named Database1. You need to design the schema for a table named table1. Table1 will have less than one million rows. Table1 will contain the…

The correct answer is int; varchar; char; date. The correct data types minimize storage: 'int' (4 bytes) is sufficient for an ID column with less than 1 million rows (max ~2.1 billion), making 'bigint' (8 bytes) wasteful. 'varchar' stores variable-length non-Unicode strings efficiently by only using space for actual…

Submitted by lukas.cz· Mar 5, 2026Design and Implement Database Objects – specifically selecting appropriate data types to minimize storage footprint in Azure SQL Database schema design.

Question

Drag and Drop Question You have a SQL Azure database named Database1. You need to design the schema for a table named table1. Table1 will have less than one million rows. Table1 will contain the following information for each row: The solution must minimize the amount of space used to store each row. Which data types should you recommend for each column? To answer, drag the appropriate data type to the correct column in the answer area. Answer:

Exhibits

70-465 question #9 exhibit 1
70-465 question #9 exhibit 2

Answer Area

Drag items

intbigintvarcharnvarcharcharsmalldatetimedate

Correct arrangement

  • int
  • varchar
  • char
  • date

Explanation

The correct data types minimize storage: 'int' (4 bytes) is sufficient for an ID column with less than 1 million rows (max ~2.1 billion), making 'bigint' (8 bytes) wasteful. 'varchar' stores variable-length non-Unicode strings efficiently by only using space for actual characters, while 'nvarchar' doubles storage with 2 bytes per character for Unicode. 'char' is appropriate for fixed-length fields (like a country code or status code) where all values are the same length, and 'date' (3 bytes) stores only date information without time, making 'smalldatetime' (4 bytes) unnecessary if time precision is not required.

Topics

#Azure SQL Database#Data Types#Schema Design#Storage Optimization

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