Data Science: A Challenge In Digital Transformation

After the pandemic, it became much more relevant and gained more presence in facilitating business decisions. But there are still challenges to be met to achieve the greatest effectiveness of this process to achieve the highest degree in the digital transformation of companies.

What is data science

Data science is a field in which advanced analytical techniques are applied to extract information from relevant data for its use in decision-making, planning, strategies or other business-related purposes.

Data processing has become much more important in companies as the years have passed. However, to benefit from it, you have to be a data scientist, and that is where all the new professions of the 21st century come in: Data Scientist, Chief Data Officer or Data Analyst.

Within data science, we will see that many disciplines and training in each is essential for one of the purposes of the company. Today, companies that operate online will find these professionals very useful because they will know what to do with all the data they manage daily.

These professionals apply Machine Learning or Artificial Intelligence (among others) to optimize the results and treat all this data more intelligently. The process is simple: information is collected, the relevant ones are chosen, they receive a treatise for their interpretation and conclusions are drawn up that indicate their usefulness or what decisions can be made through them.

Data science has not stopped growing

Within companies, the Data Scientist is an increasingly demanding professional; why? Because of the number of digital transformation projects that have emerged in the last two years. This professional’s work is key to analyzing data, and there is a lot of science behind it.

Since COVID-19 broke out, many data scientists have been dissatisfied with the company’s data analysis and modelling approach. Therefore, we must face the reality that Data Science is here to stay and the importance of these processes in digital transformation.

Digital transformation and Data Science: the stone on the road

Data science is proving to be a problem in digital transformations, and this happens because, within companies, there are not many Data Scientists. There is a lack of personnel capable of writing advanced code for cloud computing and database administration. On the other hand, the cloud does not stop growing. So, how is it possible that cloud computing services are in demand without having professionals capable of managing them? Basically, due to the need imposed by the market: the cloud offers many more facilities to companies and customers.

However, there is no optimization in using Data Science: data analysis to interpret them and use them in decision making. We are not saying this happens in all companies, but unfortunately, it does in more than the ideal ones.

It is understood that the demand for cloud computing has grown like wildfire, catching many companies off guard. Thus, many need to invest in Data Scientist teams because they add enormous value to the company and have a crucial impact on ROI, especially when processes involving Machine Learning or AI are used.