Unite Big Data and Artificial Intelligence, the key to the digital transformation of companies.

When we talk about Big Data, we can do it from different perspectives. The one we are interested in highlighting here is the one that defines it as the compendium of large volumes of data generated by any human activity plus those generated by IoT devices installed in domestic, industrial and Smart Cities environments. Machine learning capability, known as Machine Learning(ML), is an area of ​​Artificial Intelligence (AI) whose techniques learn from data. Big Data and ML complement each other. Big Data provides large volumes of data; ML techniques, specifically Deep Learning , are capable of learning from data.

Based on ML techniques we can design and train descriptive, predictive and prescriptive models. The former allow us to obtain an explanation for observed phenomena and activate alarms early. The latter allow us to anticipate predefined situations or predict certain values. Finally, the prescriptive models evaluate the risk-benefit ratio associated with each of the possible actions to be carried out.

New framework for digitization
In recent years, we have seen a strong and accelerated convergence between Big Data and Artificial Intelligence thanks to advances in technology. Advances that we can summarize in greater computing, storage and data transfer capacities at a lower cost. This is forcing both technology-based companies and any company or institution that makes strategic decisions based on intelligent data analysis, to a continuous process of adaptation to digital technologies. Aware of the need for the productive fabric to be continuously innovating, the countries has made an important commitment to the future through the new Horizon framework program . The initial budget for R&D projects is around 100 billion euros to be executed during the 2021-2027 period, and where direct or indirect investment in Artificial Intelligence is a priority.

Current scenarios for digital transformation
In this scenario outlined by the countries so oriented towards the intelligent analysis of data, and based on the rapid advances and sudden changes in the field of digital technologies that we have been observing since the beginning of the century, we can affirm that the transformation process digital is a continuum. In addition, the present moment in the technological field is characterized by the fact that Artificial Intelligence, and its application in strategic decision-making, is the high-level digital transformation that many companies expected. Transformation that really has the ability to add value to the entire value chain of any company, and that materializes by redesigning the data life cycle in all its stages from the perspective of machine learning.

Companies can no longer afford to be left behind, and delay the decision whether or not to invest in solutions based on Artificial Intelligence to make strategic decisions that allow them to be more competitive while saving costs. The question that must be asked is how to carry out this investment. In the case of non-technological companies, they must also choose which company specialized in Artificial Intelligence accompanies them in the process of integrating AI-based solutions into their value chain.

The importance of data
Artificial Intelligence experts know firsthand that the main challenge we will face in many projects is the lack of planning in the design of data capture and storage .

This lack of foresight translates, for the most part, into three major setbacks: lack of data because they are not collected regularly; changes in format and data types, because someone decided that now the data is collected in a different way than before; and lack of the output variable, that is, the values ​​of the indicators to be predicted have not been recorded. For example, if we want to detect failures in machinery, it is important to record when failures have occurred and what was the reason. It is curious how these three problems still persist today in many companies that are still questioning whether they should seriously invest in digital transformation. Transformation that must be led by the CEO of the company with the support of the CDO ( Chief Data Officer ).

We experts can see how Machine Learning techniques have already reached a very high level of maturity. They are now capable of outperforming the best results obtained by expert systems in virtually any application domain. As we have previously commented, the use of descriptive, predictive and prescriptive models based on Machine Learning to solve problems in any field is indisputable.