Let me show you why data types still matter
summary
Shows concrete bugs and fixes: a float rounding/precision case breaks a ceiling check and turns a cursor-to-set refactor from 2 minutes into 1 second but yields wrong results — lesson: float imprecision breaks monetary/counting logic. Concatenating 7,500 A + 510 B truncates because NVARCHAR halves capacity unless both sides use nvarchar(max), causing linked‑server name truncation. A table using NVARCHAR for GUIDs inflates storage from terabytes to megabytes after cleanup. Mismatched datetime2 precision blocks partition elimination and tiny SQL changes cut an ETL from 12h to <2h. Implicit conversions force index scans.
AI-written summary · about
chapters (11)
- 0:00Introduction
- 1:52Float data type surprises
- 4:45Dangers of float for precision
- 5:07String concatenation issues
- 7:39Unicode vs non-Unicode strings
- 8:24Choosing string column types
- 10:13Data types and performance
- 12:00Memory grants and data types
- 12:20Partition elimination precision
- 15:34Implicit conversion costs
- 18:00Questions and closing remarks
related talks
19mLet me show you why data types still matter- 19mLet me show you why data types still matter
46mExacting Standards: Considerations for Precision and Accuracy ...
19mNO ARRAY OF SUNSHINE: an introduction to data types from a data quality perspective
42mAdvanced Int - Bigint Conversions
46mDon't do that!
53mSQL Server Internals: The Practical Angle
52mWriting T-SQL code for the engine, not for you "more demos" by popular demand