There are numerous ways to categorize data. For one to properly filter and analyze them, they will need to know basic format classification, so that data can be properly structured. First, we have primary and secondary data classification. Primary data are information collected by you or your team while secondary are provided or collected from somewhere else. Then we have internal and external data, where internal data lives within company’s systems while external lives outside company’s systems. Then we have continuous data versus discrete data. Continuous data can have any numeric value while discrete has limited number of values. For example, number of people in a room is discrete, since you can’t have 5.5 people in a room and has to be a whole number. Height or temperature can be continuous, like being 5.57 inches tall.
There’s also qualitative and quantitative data, where quantitative is measured in numerical value while qualitative is measured in some sort of qualities or characteristics. Looking at it from data perspective, quantitative can be number of sales and qualitative can be favorite brands for specific age group. Next, we have nominal data and ordinal data. Nominal data is something that can’t be organized in a set order while ordinal is something you can organize in set order. For example, ordinal includes movie rating or income level that can be organized from high to low or low to high while nominal includes new applicant or new listing data with no way to organize them in a set order.
Understanding different data formats and how you can organize and filter them is a critical baseline skill. When you create reports, you may need to find sum of specific set of data or use some formula to get some specific numbers and not all formulas will work on specific data set. One should not only understand the types of data, but also understand where these data are pulled from, how it’s being collected and validated, and how it can be utilized for reports and dashboards.
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