Mathematical thinking

It means looking at a problem and logically breaking it down step-by-step, so you can see the relationship of patterns in your data, and use that to analyze your problem.

This kind of thinking can also help you figure out the best tools for analysis because it lets us see the different aspects of a problem and choose the best logical approach.

Big and small data

Small data

• Describes a data set made up of specific metrics over a short, well-defined time period

• Usually organized and analyzed in spreadsheets

• Likely to be used by small and midsize businesses

• Simple to collect, store, manage, sort, and visually represent

• Usually already a manageable size for analysis

Big data

• Describes large, less-specific data sets that cover a long time period

• Usually kept in a database and queried

• Likely to be used by large organizations

• Takes a lot of effort to collect, store, manage, sort, and visually represent

• Usually needs to be broken into smaller pieces in order to be organized and analyzed effectively for decision-making

The three (or four) V words for big data

They are volume, variety, velocity, and veracity.

• volume: The amount of data

• variety: The different kinds of data

• velocity: How fast the data can be processed

• veracity: The quality and reliability of the data