Data Scientist, a fashion or a trend

Data scientist has arrived not to leave any more?

Artificial intelligence, the more attractive XXI century multidisciplinary area.

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Artificial intelligence, the more attractive XXI century multidisciplinary area.
Leonardo Da Vinci, versatile and visionary pioneer in so many things said: We know very little, and yet it is surprising that we know so much.

It is even more surprising that so little knowledge give us much power.
Today, in the XXI century, Data Scientist or Scientific Data provides organizations the value added knowledge.

The data scientist will face the challenges of data to optimize the competitiveness of any business.According to the Harvard Business Review, scientific data has, therefore, the profile of the most attractive profession of this century.

For reasons of sustainability, competitiveness of any organization optimize either the private or public, with or no profit. In this context, data scientists combine knowledge of massive data and advanced analysis capabilities to achieve improved results in every one of the areas for optimization within the organization technologies In short, these professionals, the combination of knowledge, and differential add significant value to organizations.(Health organizations, pharmaceutical, home cares or any other sector)
For example enunciate, not exhaustively, some possibilities of scientific data for the performance optimization ; Increase the production of health services, improve care quality, reduce time and costs of processes, help improve intakes diagnostic and therapeutic decisions, predict as accurately as possible demand emergency service and its impact on hospitalization, consumption of consumables and staffing needs, meet mediately or immediately if it is producing an epidemic movement and its evolution, identify and anticipate the abusive and fraudulent conduct in an insurance system, systematize new forms of fraud even in the case that the event we are tracking have never occurred, improve hospital cybersecurity, predict the degree of success that is susceptible to obtain the release of a new drug, supporting the optimization of clinical practice, improving early diagnosis, … As we see., applicabilities are practically limitless.

We think that the science of data and the ability to extract knowledge is implicit in the data, it is not a fleeting fad but breaking into the world of organizations as a set of solutions, not technologies, to the needs of an organization or business and search for “disruption” or what is the same; “Upend an industry, an organization or a business (considering how it now)” consolidating into the heart of such organizations, one way to make decisions based on knowledge, this implicit knowledge in data, and is extracted from these data to give to the experts proposed or decision makers.
For example, for a private business, where customer-focused organization is replacing the product-centred organization, we will be focused, with certainty, in the micro segment, where we identify customers who have the same patterns of behavior according to a number of useful variables that explain each and every one of the behaviors identified, then we will grouped each micro segment in a region of behavior.

Thus, for each relevant behavior, we can offer our customers value propositions and new, more personal products, “proposals on demand” and manage alarms and events of different types that are of interest to our customers. We will also be very interested in having a more efficient force of sales that will thank to have opportunities and levers conversion to improve their job performance.
There are multiple technologies used in mass treatment and classification of data, but not many existing solutions to respond to the diverse needs, and we realize the opportunities for improvement identified within organizations. Now, these solutions until recently unthinkable possibilities are possible and feasible, since the costs of storage and processing of information have fallen dramatically.
In this context, the Artificial Intelligence (A.I.) stands as one of the alternatives that returns by own merits to the world of service organizations thanks to the results achieved, and thus comes to be housed in the strategic core of organizations .
Artificial Intelligence or AI, is studying the creation and design of institutions able to resolve issues themselves, using human intelligence paradigm.
Within the “umbrella” of solutions that includes artificial intelligence I want to review, although the name can be somewhat intimidating, the neural networks (ANN), these networks, indeed, hide a concept not too complicated. It is intended to mimic the performance of neural networks of living beings so that a set of connected neurons together constituted, and working together, without any have a specific task. With experience, neurons are creating and reinforcing certain connections to “learn”. But this biological approach is not very useful and networks have now, after a process of evolution, essentially mathematical and statistical focus.
The RNA are based on a simple idea, given certain parameters, there is a way to combine them to predict a certain outcome. Serve as examples; Google. Knowing the burden of servers in a central data processing (CPD), temperature and other parameters, determined that there would be a way to know about consume and servers needs, but the problem was that we do not know how to combine the different parameters. Precisely, neural networks, will allow us to find the combination of parameters best suited to solving a particular problem. This is called the neural network training. The network, once trained, can then be used to make predictions or classifications found by applying the parameters combination and substantially improve some existing results in the organization.

Luis Silva Ponte
Managing Partner
Bestprofile Management Consulting

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