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.
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.
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.
Having the required resources to manage the data needed to make decisions is crucial to the success of businesses in today's environment.
Today's data savvy organizations, those with a top-down approach to decision making, do a better job of extracting value from the data, explains a Coursera publication.
The report notes that according to Andrew Ng, Stanford professor and co-founder of Coursera, using "...data in the right way can be the path to solving critical business problems, which is the mission of business."
Using information without defined objectives and not integrating it across the entire company are part of the mistakes that organizations can make when analyzing large volumes of data.
Although there are still many companies that have not begun to analyze the information they accumulate in their operation, there is a risk that the efforts they make in the future will not achieve the expected results if the mistakes that some organizations tend to make in the process are not avoided.
The failure of polls on the presidential election in the US shows that in order to get the right information, data must be collected and analyzed with scientific rigor, free from any bias caused by the personal interest of pollsters and analysts.
EDITORIAL
Only 1 out of the 20 main pollsters, newspapers and television stations in the United States who possessed all the tools needed to properly manage the demographic data and surveys, was right in indicating who the next president would be.
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