What is event data?

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Event data is part of event-driven data architectures. Information about these events, such as the time, nature, and initiator, can be very useful for yielding business intelligence.

A hotel check-in, a single click on a website, advertisement, tweet, or any other social media post qualifies as an event. Event data comprises the timing, duration, details of the event itself, and the identity of the user, which can be processed and analyzed resulting in very valuable insights. 

Event data encapsulates these occurrences, and its main components include :

  • A timestamp.
  • Details of the action e.g. file download, order placement, add an item to cart etc.
  • Details of the user which could include a user id, name, contact information.

Benefits and applications of event data

A key feature of event data is its non-relational and straightforward structure. Since it carries information about a single instance, it does not need to arrange data. Moreover, it does not have to adhere to data types or a fixed number of attributes. A user has the liberty to place as many nested layers as required by the use case.

Event data is used to identify patterns. If a marketing agency is able to analyze a website’s user base and can categorize the age groups visiting a website, they can make an informed decision about which ads to place on the website and at what time. For example,  If a website attracts younger users, ads for trendy sneakers would intuitively be more suitable than an ad for jewelry. The time windows with the most traffic would be ideal for the advertisements instead of placing an ad for the entire day, thus saving costs for a client in case of hourly charges. 

According to a Freeman data benchmark study, senior marketing leaders are more likely to use event data for making business decisions. Around 88% of companies use event data to form other marketing strategies, 70% use it to enhance customer experience and 63% rely on it for product development. The study concludes that event data substantially helps event programs, marketing strategy, and planning. Moreover, event data can also be used to flag coordinated, inauthentic behavior on social media where a group of users attempts to artificially propagate fake news to sway public opinions. 

Event data processing example

Event data analysis can prove to be challenging; apart from being unstructured, it also arrives in bulk because of the internet’s enormous user base. To make the most of event data analysis, it is very important to process and analyze it as quickly as possible. 

Macrometa’s geo-distributed event data processing allows real-time stream processing of millions of events a second in regional and global environments.

Source: https://macrometa.com/cep/reference/overview/


It’s stream processing engine receives data event-by-event and does real-time processing to yield meaningful information such as:

  • Accept event inputs from different sources
  • Processing to transform and generate summaries, insights e.t.c.
  • Publish the results to output sinks (i.e destinations)

Summary

An event is any action on behalf of a user. The data from that action can be used to generate meaningful business intelligence and other insights.

Learn more about event-driven architectures in The Guide to Event Stream Processing.




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