What’s the Difference: Structured vs Unstructured Data
Data is growing by leaps and bounds every day — some of it is structured, but the large majority is unstructured. Estimates say that just 20% of data is structured, while unstructured data accounts for 80% of data.
In order to make meaning out of data, it has to be effectively organized, stored and analyzed. That’s why it’s important to know the nature of the data — specifically whether it’s structured or unstructured.
What is Structured Data?
Structured data is quantitative, well-organized, and easy to analyze using data analytics software. It’s formatted into systems that have a regular design, fitting into set tables,columns, and rows. Structured data also remains to predefined rules for formatting and labeling information. We usually keep structed data in the relational database(RDBMS) table columns with a fixed structure.
Characteristics:
· The structured data conform to a data model with a predefined structure.
· All data stored in a table column have similar attributes. For example, if a table contains the [FirstName] column as string data, it will always store the string data for all records in the column.
· Data is organized into entities such as tables, and these columns are linked together using relationships.
· It does not allow dynamic structure change for a specific record.
Examples of structured data include:
1. Spreadsheets
2.Relational databases such as Microsoft SQL Server, Oracle
3.Online Transaction Processing — OLTP Systems
4.Reservation Systems
What is Unstructured data?
Unstructured data is information that has no set organization and doesn’t fit into a defined framework. Examples of unstructured data include audio, video, images, and all manner of text: reports, emails, social media posts, etc.
Therefore, we cannot store them in relational databases. We can use non-relational databases such as Apache Cassandra, MongoDB, DocumentDB, Couchbase for storing unstructured data. The unstructured data might have internal structural objects, but it does not keep information in a predefined schema table format.
Characteristics:
· You do not define a specific schema or structure for data storage
· It Works with data that does not have a specific sequence
· Data is scalable and portable.
· It allows dynamic data storage for individual records.
Examples of unstructured data include:
1. Emails: The email body or message is a popular unstructured data.
2. Documents: Word files, spreadsheets, PDF, Powerpoint presentations.
3. Media files: All sorts of media files such as images, audio, video.
4. Websites: Youtube, Facebook, Instagram, LinkedIn contents can contain unstructured data such as social media messages.
5. Books, Magazines, articles, blogs, press releases etc.
6. Communication: Mobile communication data, SMS messages, live chat, IM, collaboration software.
Difference Between Structured and Unstructured Data
Structured data is stored in a predefined schema or format, whereas unstructured data is a accumulation of many different types of information.
Structured data has a fixed schema and is referred to as organized data. The information can usually easily be searched for and processed in a database.
On the other hand, the unstructured data offers flexibility and scalability without defining a fixed schema before working with any document. It allows storing data in various formats.
Structured vs. Unstructured Data: Comparison Table
The following table summarizes the difference between structured and unstructured data.
