Structured, unstructured, and semi-structured data
When working with data from data sources, how can you usefully categorize them? There are three broad categories of data: structured, unstructured, and semi-structured.
As a decision-maker, it is useful to understand the nuances and applications of structured, unstructured, and semi-structured data to make informed decisions regarding data storage, management, and analytics.
Structured data
Structured data, which is organized in a specific format such as relational databases, is easily searchable and analyzable. This type of data can include a wide range of information, such as customer names, addresses, ages, and transaction amounts, to name a few. The advantage of structured data is that it is well-defined and easier to use by data scientists and engineers, often requiring less pre-processing than other forms of data:
Figure 2.2: An example of structured data in a SQL table
