Structured data

1. Original Definition

Structured data refers to data that is organized in a well-defined format, typically in rows and columns, allowing it to be easily accessed, searched, and analyzed. It is often stored in relational databases or spreadsheets, where each element of the data is identifiable and can be categorized.

2. Simple Definition

Structured data is like neatly organized information. It’s data that’s stored in a table or spreadsheet where everything has a clear label, making it easy to find and understand.

3. Examples

Spreadsheets: Data like customer names, addresses, and phone numbers stored in rows and columns is a perfect example of structured data.
Database Records: A customer database with specific fields for name, email, and purchase history is structured data.
Inventory Systems: The information about products like price, quantity, and SKU (stock-keeping unit) is often stored as structured data in databases.
Financial Data: Bank transactions with fields such as date, amount, and account number are structured data.
Employee Records: A company’s employee database with structured fields for employee ID, name, position, and salary.

4. History & Origin

The term “structured data” emerged alongside the development of relational databases in the 1970s. It grew in importance with the work of Edgar F. Codd, who introduced the relational model for databases. This made it possible to store and query data in a structured way, revolutionizing industries like finance, healthcare, and retail.

5. Key Contributors

Edgar F. Codd: Developed the relational database model, which formed the basis for structured data storage and querying.
Larry Ellison: Co-founded Oracle, a company that popularized relational databases and structured data in business applications.
Michael Stonebraker: A pioneer in database systems who helped shape the development of modern database management systems.

6. Use Cases

Business Analytics: Companies use structured data in databases to track performance, sales, and customer behavior.
Customer Relationship Management (CRM): Structured data is used in CRM systems to manage customer interactions and data efficiently.
Healthcare Systems: Hospitals use structured data to manage patient records, treatments, and prescriptions in an organized way.
E-Commerce: Online stores use structured data to manage product catalogs, prices, and stock availability.
Search Engines: Google uses structured data (like schema markup) to enhance search results and provide more relevant information to users.

7. How It Works

Structured data is stored in a well-organized format, typically within rows and columns in a table or a spreadsheet. Each column represents a specific data type (e.g., name, date, amount), and each row represents a record. This organization allows for quick data retrieval, sorting, filtering, and analysis. For instance, a database query can be used to quickly find all transactions above a certain amount by looking through the rows of data.

8. FAQs

Q: How is structured data different from unstructured data?
A: Structured data is organized and easily searchable, typically in a table format. Unstructured data, on the other hand, is messy and doesn’t follow a set format, like emails, videos, or social media posts.

Q: Can structured data be used in artificial intelligence?
A: Yes! Structured data is often used in AI and machine learning to train algorithms, as it’s easier for systems to process and analyze.

Q: What are the advantages of structured data?
A: Structured data is easy to search, analyze, and process due to its organized format. It enables quick decision-making and efficient reporting, making it valuable in business applications.

9. Fun Facts

Structured data makes up only about 20% of all data today; the rest is unstructured.
Relational databases that store structured data are often compared to spreadsheets because both use a table format.
Some of the most commonly used structured data formats include CSV (Comma Separated Values) and SQL (Structured Query Language).
Structured data helps power personalized ads by organizing customer behavior data into easy-to-read formats.
Before databases, companies stored structured data on paper in file cabinets.
In e-commerce, structured data like product prices and availability helps search engines display rich snippets in search results.
Structured data is often used in financial systems for things like tracking investments and profits.
The process of creating structured data is often automated, particularly in big data systems.
It’s essential in industries like banking, where data organization and precision are critical.
Most of the world’s financial data, including stock prices, is stored as structured data.