Behavior analysis is a type of data analysis that tries to understand how and why people behave that way. Behavior analysis measures how consumers relate to digital applications (e-commerce, mobile, social media, gaming, IoT). Data such as demographics or past activities are collected to generate insights and predict future trends. The principles of behavior analysis are applied not only to the behavior of people, but also to the interactions and dynamics between processes, machines, equipment, and even macroeconomic trends.
Behavioral analytics combines typical event tracking with audience segmentation to associate users with triggered events and map customer journeys, using the large amount of raw data collected by the analytics platform.
Behavior Analysis is an important subset of business analytics that helps us understand how and — why — consumers and apps behave this way. It is particularly prevalent in e-commerce, online gaming, web, mobile and IoT applications — and provides the data needed to improve the customer journey towards transformation.
Behavior analytics measure data such as navigation paths, clicks, social media interactions, and purchase/cart abandonment. A/B testing is an example of using analytics to make data-driven decisions.
Cloud migration, one of the most important components of digital transformation, is the process of moving an organization's existing data, applications, and infrastructure to a cloud-based environment.
Foundation Models (FMs) refer to structures trained on large data sets in the field of artificial intelligence and machine learning, versatile and usable in a variety of applications.
Green Computing is a comprehensive approach that aims to minimize the environmental impact over the entire lifecycle, from the design of information technologies to their production, from use to disposal.
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