Using a mathematical approach doesn't mean you have to suddenly become a math whiz. It means looking at a problem and logically breaking it down step-by-step

When working with data, you'll find that there's big and small data.

Small data

Small data can be really small.

• These kinds of data tend to be made up of datasets concerned with specific metrics over a short, well-defined period of time.
• Small data can be useful for making day-to-day decisions.
• But it doesn't have a huge impact on bigger frameworks like business operations.
• You might use spreadsheets to organize and analyze smaller datasets when you first start out.
• Specific
• Short time-period
• Day-to-day decisions

Big data

• on the other hand has larger, less specific datasets covering a longer period of time.

• They usually have to be broken down to be analyzed.

• Big data is useful for looking at large-scale questions and problems, and they help companies make big decisions.

• When you're working with data on this larger scale, you might switch to SQL.

• Large and less-specific

• Long time-period