Understanding Data Types in the Modern Economy
In today's data-driven economy, businesses are inundated with information from thousands of sources, including CRMs, web apps, IoT devices, social media, internal systems, and third-party APIs.
To make sense of this information and drive smarter decisions, organizations must understand how data is categorized and handled.
Three Categories of Data
Broadly, data falls into three categories:
Structured Data
Data that is organized in a predefined format, typically with a well-defined schema.
Examples:
- Database records (SQL)
- Spreadsheets
- CRM data
- Financial transactions
Unstructured Data
Data with no predefined structure or organization, making it more difficult to collect, process, and analyze.
Examples:
- Text documents
- Emails
- Social media posts
- Images and videos
Semi-Structured Data
Data that does not conform to a formal structure but contains tags or markers to separate elements.
Examples:
- JSON files
- XML documents
- HTML code
- NoSQL databases
Key Considerations
- Each type requires different storage solutions, processing techniques, and analytics tools.
- Let's break down the characteristics, advantages, and trade-offs, and how to make sure your data stack is ready for all three.
- We'll examine structured data vs unstructured data vs semi-structured data, looking at the key differences, use cases, and business value for each.
Continue Your Learning Journey
Understanding these data types is crucial for building effective data management strategies and choosing the right tools for your organization's needs.
Read Full Article at Matillion