In the digital era, data is being created at a speed never seen before, and its proper application in business intelligence is already generating incalculable value for businesses
It seems irrational to suggest that a concept like data could be more valuable than an established and indispensable product like oil, but as the years have gone by, this already seems like a reality.
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.
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.
To effectively apply data analysis tools on a large scale, the proper structuring of the information is essential, otherwise the cost that the company will have to incur to reverse the errors will be very high.
Data governance, which encompasses the set of processes, functions, policies, standards and measurements that ensure the effective and efficient use of information, becomes relevant to enterprises, which increasingly benefit from the use of machine learning tools and statistical analysis.
The ability to identify and understand hidden patterns and correlations in large volumes of data and use them to make business decisions is becoming a strategic competition for companies for the future.
Machine learning and statistical analysis are some of the most popular techniques used today in artificial intelligence (AI) applications. Automatic learning is the AI technique for identifying hidden patterns and correlations in a large amount of data that humans cannot identify on their own, explains Brian Ka Chan, technology strategist and researcher at Smart City.