Predicting the future can generate good business

After the Big Data and Analytics, another area of ​​computing has attracted the attention of the corporate world: Machine Learning, dedicated to the study and pattern recognition and machine learning

The amount of collected and stored data continues to grow at a blistering pace. Every day, more devices are monitoring equipment, environmental conditions and human activities, increasing the volume of data by almost 50% per year. From the point of view of business, it is clear that it is not enough to accumulate a huge amount of data, but you need to know what to do with all that information. If you rely on forecasts of some IT experts, it’s time the “digital prophecy” gain space in the world in business.

For some time, companies are using Big Data and Analytics capabilities to identify previously undetectable and complex relationships between large clusters of information. Recently, another area of ​​computing has attracted the attention of the corporate world: it is the Machine Learning, dedicated to the study and pattern recognition and machine learning. By combining these two features you can create intelligent algorithms able to make predictions or make decisions from data inputs, instead of following static instructions previously established.

Just a few examples to get an idea of ​​the impact of these technologies in terms of business. The ability to recognize abnormalities scenarios in financial transactions can facilitate the identification of fraud even before the transaction is completed, for example. Mapping the e-commerce user profile and predict behavior patterns enables the supply of goods and services from the interest and real willingness to purchase a potential customer at any given time.

Some more conservative profile areas are also making use of technology. Insurance companies, for example, begin to identify more precisely the people offering potential risk, facilitating the analysis assured future profile. The financial investment industry is one that will be influenced by the Machine Learning. Indeed, several initiatives are already getting predict the behavior of actions from economic variables.

Even the productive sector should be impacted. Nowadays, it is possible to predict the approximate time when a specific equipment will fail to operate efficiently or even crashing. A company can thus plan the replacement parts in advance, based on the performance of the equipment and not their average life expectancy.

Forecast results in elections from research done by social networks are anticipating, surprisingly, election results. The health sector must also undergo major changes. It is possible, for example, to anticipate the likelihood of emergence of epidemics from analysis of risk factors. In brief, it is also possible to provide, through the analysis of synapses, the relative risks to the development of memory and dementia disorders, such as Alzheimer’s, in asymptomatic populations.

These technologies are much more interconnected than it may seem at first. You need to know how to combine the resources and apply them to every problem and objective, enabling preventive action rather than reactive. In this way, one can prevent the emergence of problems that may compromise the integrity of administrative processes of a company.

Full article: http://cio.com.br/

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