Predictive Analytics For Dummies
Book image
Explore Book Buy On Amazon
Data for a predictive analytics project can come from many different sources. Some of the most common sources are within your own organization; other common sources include data purchased from outside vendors.

Internal data sources include

  • Transactional data, such as customer purchases

  • Customer profiles, such as user-entered information from registration forms

  • Campaign histories, including whether customers responded to advertisements

  • Clickstream data, including the patterns of customers’ web clicks

  • Customer interactions, such as those from e-mails, chats, surveys, and customer-service calls

  • Machine-generated data, such as that from telematics, sensors, and smart meters

External data sources include
  • Social media such as Facebook, Twitter, and LinkedIn

  • Subscription services such as Bloomberg, Thompson Reuters, Esri, and Westlaw

By combining data from several disparate data sources in your predictive models, you may get a better overall view of your customer, thus a more accurate model.

About This Article

This article is from the book:

About the book authors:

Anasse Bari, Ph.D. is data science expert and a university professor who has many years of predictive modeling and data analytics experience.

Mohamed Chaouchi is a veteran software engineer who has conducted extensive research using data mining methods.

Tommy Jung is a software engineer with expertise in enterprise web applications and analytics.

This article can be found in the category: