Big data analytics is an effective solution for identifying behavioral patterns and establishing strategies to help detect and prevent fraud in various business sectors.
Most companies are not aware of the information they have and how to leverage, analyze and understand it, which can result in the loss of a large amount of potentially useful data by normalizing fraud and other criminal activities in their processes and make them difficult to prevent and detect.
Thanks to the digitalization of writing and the rise of Internet searches and interactions, words have become very valuable inputs for statistical models and algorithms that allow inferring and reaching very precise conclusions about consumer behavior, among other uses.
Today, language has become the subject of big data analysis. Since the links used by Google are composed of words and the searches performed on that page are also composed of words, the study of text as data is becoming increasingly important.
Analyzing satellite photos to estimate the production capacity of an area or evaluating images of a product being sold on the streets to calculate its market-share are some of the business solutions that arise from the transformation of images into data.
Traditionally, when teachers or businessmen wanted data, they requested surveys. Data would be ordered, in the form of numbers or boxes checked on questionnaires.
Does it make sense to keep doing surveys to evaluate, for example, the ranking of a brand, when all the real, honest, and unbiased information can be inferred from people's behavior on the Internet?
"... Traditionally, when teachers or business people needed data, they commissioned surveys. They obtained data in an orderly fashion, either in figures or in boxes marked on questionnaires.
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