The qualitative data interpretation method is used to analyze qualitative data, which is also known as categorical data. There are 2 main methods in which this can be done, namely quantitative methods and qualitative methods. market size, growth rate, etc.) for better understanding. Data, when collected in raw form, may be difficult for the layman to understand, which is why analysts need to break down the information gathered so that others can make sense of it.įor example, when founders are pitching to potential investors, they must interpret data (e.g. Therefore, researchers have identified some data interpretation methods to aid this process.ĭata interpretation methods are how analysts help people make sense of numerical data that has been collected, analyzed and presented. It is evident that the interpretation of data is very important, and as such needs to be done properly. It is usually the first step taken towards data interpretation. What then, is data analysis?ĭata analysis is the process of ordering, categorizing, manipulating, and summarizing data to obtain answers to research questions. Therefore, before one can talk about interpreting data, they need to be analyzed first. It involves taking the result of data analysis, making inferences on the relations studied, and using them to conclude. What is Data Interpretation?ĭata interpretation is the process of reviewing data through some predefined processes which will help assign some meaning to the data and arrive at a relevant conclusion. So, what is data interpretation and analysis, and how do you leverage this knowledge to help your business or research? All this and more will be revealed in this article. Also, all these need to be done in milliseconds. According to the WEF’s “A Day in Data” Report, the accumulated digital universe of data is set to reach 44 ZB (Zettabyte) in 2020.īased on this report, it is clear that for any business to be successful in today’s digital world, the founders need to know or employ people who know how to analyze complex data, produce actionable insights and adapt to new market trends. Data interpretation and analysis are fast becoming more valuable with the prominence of digital communication, which is responsible for a large amount of data being churned out daily.
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