In this book, you have learned a lot about SQL's processing power over numbers and strings. The majority of data analytics tasks are indeed analyzing numbers and strings. However, in the real world, data is often found in various other formats, such as words, locations, dates, and, sometimes, complex data structures. This data, although presented as numbers and strings, has its own domain of operation and computation instead of simple arithmetic. For example, adding one day to January 31, 2022, will result in February 1, 2022, not January 32, 2022.
In this chapter, you will look at these data types and examine how you can use this data in your analysis:
- Date and time
By the end of the chapter, you will have broadened your analysis capabilities so that you can leverage just about any type of data available to you.