Structured data is the data which conforms to a data model, has a well define structure, follows a consistent order and can be easily accessed and used by a person or a computer program.
Structured data is usually stored in well-defined schemas such as Databases. It is generally tabular with column and rows that clearly define its attributes.
SQL (Structured Query language) is often used to manage structured data stored in databases.
Characteristics of Structured Data:
- Data conforms to a data model and has easily identifiable structure
- Data is stored in the form of rows and columns
Example : Database
- Data is well organised so, Definition, Format and Meaning of data is explicitly known
- Data resides in fixed fields within a record or file
- Similar entities are grouped together to form relations or classes
- Entities in the same group have same attributes
- Easy to access and query, So data can be easily used by other programs
- Data elements are addressable, so efficient to analyse and process
Sources of Structured Data:
- SQL Databases
- Spreadsheets such as Excel
- OLTP Systems
- Online forms
- Sensors such as GPS or RFID tags
- Network and Web server logs
- Medical devices
Advantages of Structured Data:
- Structured data have a well defined structure that helps in easy storage and access of data
- Data can be indexed based on text string as well as attributes. This makes search operation hassle-free
- Data mining is easy i.e knowledge can be easily extracted from data
- Operations such as Updating and deleting is easy due to well structured form of data
- Business Intelligence operations such as Data warehousing can be easily undertaken
- Easily scalable in case there is an increment of data
- Ensuring security to data is easy
Note: Structured data accounts for only about 20% of data but because of its high degree of organisation and performance make it foundation of Big data
To read Differences between Structured, Semi-structured and Unstructured data refer the following article –
- Difference between Structured, Semi-structured and Unstructured data
- What is Semi-structured data?
- Large objects(LOBs) for Semi Structured and Unstructured Data
- Structured Query Language (SQL)
- Difference between Data Scientist, Data Engineer, Data Analyst
- How Big Data Artificial Intelligence is Changing the Face of Traditional Big Data?
- Characteristics of Biological Data (Genome Data Management)
- Does Dark Data Have Any Worth In The Big Data World?
- Difference between Data Warehouse and Data Mart
- Difference between a Data Analyst and a Data Scientist
- Difference between Data Warehousing and Data Mining
- Types of Sources of Data in Data Mining
- Data Mining: Data Attributes and Quality
- Data Mining: Data Warehouse Process
- Data Preprocessing in Data Mining
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