What Is a Data Source?

Key takeaways

A data source indicates the point of origin for a specific set of information.

• Data sources help compile information into accessible formats, which enables seamless integrations between different types of systems.

• When dealing with big data, you can divide most data sources into two categories: machine data sources and file data sources.

• You can develop your data source knowledge for a career in data analysis.

Learn more about data sources, including the important role of data sources and where data originates. If you’re considering working in the data analytics industry, enroll in the Google Data Analytics Professional Certificate, where in as little as six months, you can learn about data visualization, data storytelling, Tableau software, and more.

What is a data source?

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.

What is an example of a data source?

Data can originate from various sources, including data warehouses, relational databases, Internet of Things (IoT) devices, Microsoft Excel spreadsheets, and web scraping tools. Source data is also known as raw or primary data.

Read more: What Is the Internet of Things (IoT)? With Examples

Types of data sources

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, 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

• Metadata

• Database

• Dashboard

• Data integrity

• Business intelligence

Explore trends and job opportunities in data analytics

If you’d like to keep up with trends and job opportunities in the field of data analytics, subscribe to Career Chat on LinkedIn. These other free resources might also be helpful to you:

• Watch on YouTube: 3 High-Paying Career Paths After Google Data Analytics Certificate

• Ask an expert: 6 Questions with a Microsoft Data Analytics Leader

• Learn the terminology: Data Analysis Terms & Definitions

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