During user-acceptance testing, a query that adds 0.10 and 0.20 stored in a staging table returns 0.30000000000000004 instead of the expected 0.30. The developer confirms that the values were inserted as decimal literals but did not explicitly set a fixed-precision data type on the column. Which column data type definition is MOST likely causing this anomaly?
The column was defined as FLOAT, an approximate numeric type that stores values in IEEE-754 binary floating-point format. Many base-10 fractions such as 0.10 or 0.20 cannot be represented exactly in binary, so the database stores the closest binary approximation. When those approximations are added, the tiny representation errors become visible-e.g., 0.10000000000000001 + 0.20000000000000001 ≈ 0.30000000000000004. Fixed-precision types like DECIMAL, NUMERIC, or MONEY store decimal fractions exactly to their declared scale, so they would return 0.30 without the extra digits.
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What is the IEEE-754 binary floating-point format?
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How do fixed-precision data types like DECIMAL or NUMERIC prevent precision errors?
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CompTIA Data+ DA0-002 (V2)
Data Concepts and Environments
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