#data management
Qualitative data is data that isn’t measured in numbers
Data is information, and when we look at it through that lens, it’s easy to see that not every single byte of information can be measured in discrete numbers or measured
For example, if I asked you what people think of your client’s products, you might be able to say the outlook is positive, and prove it by showing measurable quantities typically associated with a positive outlook, but you wouldn’t be able to quantify the positivity itself
Qualitative data is important because it points us in the direction of the story the data is telling, and offers us powerful touch points to connect with the lives behind the data we work with
For an exact science, data analytics relies a lot on qualitative data, and it is important as a data analyst to know how to handle, sift and leverage qualitative data
Qualitative data will often call for sentiment analysis (designed to give you an overview of the general mood). Qualitative data can provide insight into why outliers are outliers, why seemingly satisfied clients leave the brand, the “sudden” onset of an unexpected phenomenon and is very useful to executives for decision making
(more stressful too, but good things require work)
Questions? Drop them in the comments