Understanding the Types of Data in Data

Summary

Key Takeaways Data can be classified into qualitative (descriptive) and quantitative (numerical) types, which require different analysis methods. Data is also categorized as structured (organized), unstructured (disorganized), or semi-structured (partially organized). Some of the most relevant types of big data used in today’s data science processes include transactional, machine, social, and text data. The three Vs of big data—Volume, Variety, and Velocity—define the challenges of managing large, diverse, and rapidly generated data. For some, data is simply another word for information—and while that’s not entirely wrong, there’s a bit more to it. Data refers to raw facts and figures collected through observation, measurement, or experimentation. On its own, it may not mean much. But, when processed, analyzed, and placed in context, that data transforms into something meaningful. The word itself may be short, but the meaning of data extends across a broad spectrum of information that can be divided into several distinct types. Researchers, analysts, and professionals then use a variety of these types of data to identify patterns, test hypotheses, make predictions, and inform decisions, among other uses. What Are the Different Types of Data? Each data type serves a different purpose and requires different methods for analysis and application. Understanding the distinctions is important for all working in data science, statistics, or any other field that relies on data-driven insights. Quantitative data The term quantitative refers to something that is related to quantities or amounts. So, based on that, data that is classified as quantitative means the information is expressed in numbers—it’s the type of data that we can measure or count. Such data is all around us—think about how we track our expenses, measure the length of a table, or even count the number of people attending a meeting. This type of data is mainly used in fields like statistics and research becaus...