Ideation

The first step in any data problem is to identify what it is you want to figure out. This is referred to as ideation, of coming up with an idea of what we want to do and prove. Ideation generally relates to hypothesizing about patterns in data that can be used to make intelligent decisions.

These decisions are often within the context of a business, but also within other disciplines such as the sciences and research. The in-vogue thing right now is understanding the operations of businesses, as there are often copious amounts of money to be made in understanding data.

But what kinds of decision are we typically looking to make? The following are several questions for which answers are commonly asked:

• Why did something happen?
• Can we predict the future using historical data?
• How can I optimize operations in the future?

This list is by no means exhaustive, but it does cover a sizable percentage of the reasons why anyone undertakes these endeavors. To get answers to these questions, one must be involved with collecting and understanding data relative to the problem. This involves defining what data is going to be researched, what the benefit is of the research, how the data is going to be obtained, what the success criteria are, and how the information is going to be eventually communicated.

pandas itself does not provide tools to assist in ideation. But once you have gained understanding and skill in using pandas, you will naturally realize how pandas will help you in being able to formulate ideas. This is because you will be armed with a powerful tool you can used to frame many complicated hypotheses.