Articles & Resources > Business Intelligence >

Big Data: 6 Unusual Ways Companies Can Collect Your Data

Big Data: 6 Unusual Ways Companies Can Collect Your Data

A woman on her computer looking over her shoulder under the watchful eye of a large security camera right next to her.

Last Updated March 8, 2024

Big Data Collections

Big data has been hailed as a global game changer in the tech industry, giving businesses and governments quantifiable information on just about everything people choose to do online. But big data goes beyond cookies and web tracking.

The use of big data can give businesses interesting, and sometimes surprising, insights into our lives. This article highlights some of the more unusual ways big data is collected.

 

Loyalty Card Data Collection

1. Loyalty Cards

Using loyalty cards can also carry some benefits, as it rewards repeat customers and incentivizes more shopping.

That said, customers should be aware that each time they use loyalty or credit cards, their purchase data is being tracked and stored.

While it may make sense for retailers to understand which products are being sold to different groups of customers, this information can also be used to create detailed customer profiles that can then be sold to advertisers and other businesses.

2. Gameplay

Online gamers are not exempt from big data collection.

The constant web connection of devices allows game developers to access large amounts of data instantaneously, even if the game is otherwise single-player.

Every time a user has difficulty on a particular level, makes an in-app purchase, installs or deletes the game, plays for a long stretch of time or gives up after a few minutes, this information is tracked and stored.

 

3. Satellite Imagery

One interesting source of big data is what can be visible from the sky. With the development of Google Earth and Google Maps, satellite data is now publicly available. This allows savvy analytics professionals to develop surprisingly complete pictures of certain areas and even begin to understand the types of people who live and work in those locations.

4. Employer Databases

HR departments can use big data to profile their employees and quantify workplace performance. Employee history with the company might be an common interest, but big data also includes less intuitive figures, including:

  • The amount of time workers spend with certain programs on their computers
  • The times of day where employees appear most active
  • The moment employees first power on their devices

Information documented with technology can often find some use in big data sets and help create an image of employee quality.

>> Explore big data with a certificate in Business Analysis

Data Spying

5. Your Inbox

Modern email services are depositories of large amounts of user data.

While the following information is not true of all services, it is the case in some of the most popular email providers, including Google and Yahoo. Both of these companies use algorithms to scan the content of your email for certain keywords with the goal of providing advertising targeted toward your interests.

For example, this may include links for hotel reservations after you received an email discussing an upcoming trip.

>> Learn about Villanova’s Certificate in Business Intelligence

6. Social Media Activity

Social media sites are another large provider of big data. Social media users often willingly provide information about their personal lives to such services, and Terms of Service agreements typically allow sites the right to store and use this information as they see fit.

However, big data analytics can also be used to document which features users agree to disable, which posts they delete and how often they log into the site at different parts of the day. This information can be used to create thorough profiles of users’ habits and detail what information is important to them.

Using Big Data

From online usage and apps to credit cards and satellite imagery, companies are now able to package our lives into increasingly large data sets. Yet, collecting all of this data is one thing – using it to learn more about customers’ tendencies is another. The next article in this series will focus on some of the insights these large data sets can provide.