What is external data?

External data is data collected from sources outside your organization (aka the cool data 😎). The data could be:

  1. Publicly available data such as census, administrative data, information from government departments (housing, electoral statistics, tax records) and internet searches.
  2. Private data owned by third parties such as Amazon, Facebook, Google, Walmart and credit reporting agencies like Experian.

Like internal data, external data can be primary or secondary.

When you conduct interviews with industry leaders, you're collecting primary data from an external source. So, such data is external and primary.

When you use the interviews conducted by an external source (let's say a newspaper), then you're using data that's external and secondary.

Why is external data important?

The advantage of external data is that it gives any organization the ability to access and mine data for insights without having to worry about storing or managing all of that data. As such, organizations can make decisions faster with significantly fewer resources.

When you use external data collected by third-party agencies (like Atlan Grid, for example), it's already cleaned and processed, making it ready for analysis. In general, external data is richer and often, more complex than internal data.

What are the risks of using external data?

External data comes with its own set of limitations. It might not be specific to your needs and by itself, external data isn't enough to reach a conclusion.

When another agency creates it, it might not be wholly accurate. In such cases, the risks of an external data set containing errors are quite high and you should be careful while cleaning it for further analysis.

When you use private external data, you must pay for access and rely on an external source for decision-making. That's why you should weigh the pros and cons of external data carefully before deciding to use external data.

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See also

Articles you might be interested in

  1. Why external data is the fuel of tomorrow's business success
  2. How third-party information can enhance data analytics
  3. Primary and secondary data: Definition and example