The CAST and CONVERT functions are essential SQL tools used to change data from one type to another, a process known as type conversion or data type casting. These functions are particularly valuable when cleaning and processing data to ensure consistency and compatibility across your datasets.
Th…The CAST and CONVERT functions are essential SQL tools used to change data from one type to another, a process known as type conversion or data type casting. These functions are particularly valuable when cleaning and processing data to ensure consistency and compatibility across your datasets.
The CAST function follows ANSI SQL standards and uses a straightforward syntax: CAST(expression AS data_type). For example, if you have a number stored as text and need to perform mathematical calculations, you would use CAST(column_name AS INTEGER) to transform it into a numeric format. This function works across most database systems including BigQuery, MySQL, and PostgreSQL.
The CONVERT function offers similar functionality but with slight variations depending on the database platform. In SQL Server, CONVERT provides additional formatting options, especially useful for date and time conversions. The syntax typically follows: CONVERT(data_type, expression, style). The style parameter allows you to specify particular formats for dates or numbers.
Common use cases for these functions include converting strings to dates when date information was imported as text, changing numeric values between integer and decimal formats, transforming numbers to strings for concatenation purposes, and standardizing data types before joining tables.
When working with dirty data, type mismatches frequently cause errors and unexpected results. A column that should contain numbers might have text entries, or dates might be formatted inconsistently. Using CAST or CONVERT helps resolve these issues during the data cleaning process.
Best practices suggest using CAST for standard conversions due to its broader compatibility across database systems. Reserve CONVERT for situations requiring specific formatting options available in your particular database platform. Always verify your conversions produce expected results, as invalid conversions can generate errors or NULL values that might affect your analysis outcomes.
CAST and CONVERT Functions: Complete Guide for Google Data Analytics
Why CAST and CONVERT Functions Are Important
In data analytics, you frequently encounter data stored in formats that don't match your analysis needs. For example, numbers might be stored as text strings, or dates might need to be reformatted for calculations. CAST and CONVERT functions are essential tools that allow you to transform data types, ensuring accurate calculations, proper sorting, and meaningful comparisons.
What Are CAST and CONVERT Functions?
CAST and CONVERT are SQL functions used to change data from one data type to another. This process is called type conversion or type casting.
CAST Function: The CAST function is the ANSI SQL standard for converting data types. It works across most database systems including BigQuery, MySQL, PostgreSQL, and SQL Server.
Syntax: CAST(expression AS data_type)
CONVERT Function: The CONVERT function is specific to certain database systems like SQL Server and MySQL. It offers additional formatting options, particularly for date and time conversions.
Syntax: CONVERT(data_type, expression, style)
How These Functions Work
Common Use Cases: • Converting strings to numbers for mathematical operations • Converting numbers to strings for concatenation • Changing date formats for reporting • Converting between integer and decimal types
Examples:
1. String to Integer: SELECT CAST('123' AS INT64) Result: 123
2. Number to String: SELECT CAST(456 AS STRING) Result: '456'
3. Float to Integer: SELECT CAST(99.7 AS INT64) Result: 99 (truncates decimal portion)
4. String to Date: SELECT CAST('2024-01-15' AS DATE) Result: 2024-01-15
Key Differences Between CAST and CONVERT
• CAST is standard SQL and more portable across databases • CONVERT offers style parameters for formatting (mainly in SQL Server) • CAST uses the keyword AS between value and target type • CONVERT uses commas to separate parameters
Exam Tips: Answering Questions on CAST and CONVERT Functions
1. Know the Syntax Differences: Remember that CAST uses AS (CAST(value AS type)) while CONVERT uses commas. Exam questions often test whether you can identify correct syntax.
2. Understand Data Type Compatibility: Not all conversions are possible. You cannot convert 'hello' to an integer. Questions may present invalid conversions as answer options.
3. Remember Truncation Behavior: When converting decimals to integers, values are truncated, not rounded. CAST(9.9 AS INT) equals 9, not 10.
4. Focus on CAST for Google Data Analytics: BigQuery primarily uses CAST, so prioritize understanding this function for the certification exam.
5. Watch for Context Clues: Questions often describe a scenario where data types mismatch. Look for phrases like 'stored as text' or 'needs to be calculated' to identify when type conversion is needed.
6. Practice Common Conversions: • STRING to INT64 or FLOAT64 • Numeric types to STRING • STRING to DATE or TIMESTAMP
7. Be Careful with NULL Values: CAST returns NULL if the input is NULL. This is a common exam topic.
8. Review Error Handling: Know that invalid conversions cause errors. Some databases offer SAFE_CAST which returns NULL instead of an error for failed conversions.
Practice Question Approach: When you see a question about data type issues, first identify what type the data currently is, then determine what type it needs to be, and finally select the appropriate CAST or CONVERT syntax.