The NoSQL arena has many options, ranging from simple object storage to complex document and graph-based data stores. 

There are several different basic data types and it’s important to know what you can do with each of them so you can collect your data in the most appropriate form for your needs. People describe data types in many ways, but we’ll primarily be using the levels of measurement known as nominal, ordinal, interval, and ratio.

If you look around the internet or in textbooks for info about data, you’ll often find variables described as being one of the data types listed above. Be aware that many variables aren’t exclusively one data type or another. What often determines the data type is how the data are collected

When trying to turn data into information, the data you start with matter a lot. Data can be simple factoids—of which someone else has done all of the analysis—or raw transactions, where the exploration is left entirely to the user.

Gathering data is similar to gathering ingredients for a recipe. If you want to create an excellent dish, you’ll want to start with the right ingredients, which means you’ll have to make a bunch of decisions beforehand.

After you’ve decided what type of survey you’re going to use, you need to figure out what kinds of questions to include. The type of question determines what level of data can be collected, which in turn affects what you can do with the data later on. For example, if you ask about age and you record it as a number (e.g., 21, 34, 42), you’ll have numeric data that you can perform mathematical operations on. If you instead ask for a person’s age group (e.g., 18-24, 25-34, 35-44), you’ll have ordered categorical data: you’ll be able to count how many people were in each group, but you won’t be able to find the mean age of your respondents. Before you create your survey, it’s important to consider how you want to analyze your final results so you can pick question types that will give you the right kind of data for those analyses.

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