What Is a Data Source?

Written by Coursera Staff • Updated on

Learn the significance of data sources in data analytics and why they’re important for a successful data analysis strategy.

[Featured image] A data analyst presents visualizations from a company data source on a large digital screen.

A data source refers to the origin of a specific set of information. As businesses increasingly generate data year over year, data analysts rely on different data sources to measure business success and offer strategic recommendations. Having data literacy means you’re capable of identifying, understanding, and interpreting crucial data and its results.

Data sources play a key role by bundling information into accessible formats, which enables seamless integrations between different types of systems. This ensures that relevant information about a data set is readily available while remaining hidden, allowing analysts to focus on data interpretation and analysis.

Extremely large data sets used by data analysts are called big data, and they require a framework that scales with their volume and variability. Within big data, most data sources separate into two main categories based on the data’s storage, access, and use: machine data sources and file data sources.

  • Machine data sources are labeled by users, stored in the input machine, and not easily shareable. The data source integrates with various components essential for accessibility, like the server location and driver engine.

  • File data sources reside within single, shareable files, allowing multiple users to access and edit the data from different locations.

These data sources can be further classified into smaller categories:

  • Internal data: Created by organizational processes, including email marketing, customer profiles, and online activity

  • External data: Derived from outside sources like social media, historical demographic data, and websites

  • Third-party analytics: Provided through analytics platforms like Google Analytics

  • Open data: Free, public-accessible data, like government and health and science data

Data analysts transport this data through several methods, including file transfer protocol (FTP) and hypertext transfer protocol (HTTP). Websites provide application programming interfaces (APIs) to allow people to transfer data sets from their platforms.

Related terms

Learn more about data sources

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