Types of Data Sources

Following are some of the data sources in data science process-

1. Structured Data: Structured data is organized and formatted in a predefined manner, usually in tabular form with rows and columns. Databases and spreadsheets are common sources of structured data. This type of data is easy to analyze and query. 

2. Unstructured Data: Unstructured data lacks a predefined structure and is typically found in the form of text, images, audio, and video files. Social media posts, emails, and documents are examples of unstructured data sources. Analyzing unstructured data often requires advanced natural language processing (NLP) and computer vision techniques.

3. Semi-Structured Data: Semi-structured data has some level of structure, such as XML or JSON files, but does not conform to a strict schema like structured data. Web pages, log files, and certain types of documents are sources of semi-structured data.

4. Time-Series Data: Time-series data records observations over time at regular intervals. It is commonly used in applications where data points are captured sequentially, such as financial markets, weather data, and sensor readings.

5. Geospatial Data: Geospatial data contains location-based information and is often represented using coordinates, such as latitude and longitude. It is utilized in mapping, navigation, and location-based services.