Learning Google BigQuery

Data type considerations

Let's further discuss these data types:

• Floating-point: Unlike integers, which must be whole numbers, floating-point numbers can have fractional components and can have special non-numeric values such as NaN (not a number), Inf (infinite), or null.

In order to avoid non-numeric values, make sure your mathematical calculations deal with non-numerics using the IFNULL() and <IFNULL(FUNCTION,0)> function for Legacy SQL. For Standard SQL, wrap the IFNULL() function around the SAFE_DIVIDE() function for situations such as dividing zero by zero.

• String: Don't store all values as string in the table. Use appropriate data types, for example for TRUE or FALSE use Boolean type instead of storing the value as string. 
• Date ...