The big data platform can obtain structured transaction data with longer time span and larger volume, so that it can analyze a wider range of transaction data types, including not only POS or e-commerce shopping data, but also behavioral transaction data, such as Internet click stream data logs recorded by Web servers.

Human-generated data

Unstructured data widely exists in e-mail, documents, pictures, audio, video and data streams generated through blogs, wikis, especially social media, which provide rich data sources for text analysis.

Mobile data (mobile data)

Smartphones and tablets with Internet access are becoming more and more popular. Applications on these mobile devices can track and communicate countless events, from transaction data in applications (such as the recorded events of searching products) to personal information or status reporting events (such as reporting new geocodes when the location changes).

Machine and sensor data.

This includes data created or generated by functional devices, such as smart meters, intelligent temperature controllers, factory machines and household appliances connected to the Internet. These devices can be configured to communicate with other nodes in the Internet, or they can automatically transmit data to the central server for data analysis.

What are the main data types of big data analysis? Ivy Bian Xiao will share with you here. If you are interested in big data engineering, I hope this article can help you. If you want to know more about the skills and information of data analysts and big data engineers, you can click on other articles on this site to learn.