Large companies, whatever their size, are in need of facing a transformation process that is changing the fundamentals of the entire industry. It is also an inevitable and global revolution, that does not understand about sectors and industries. Today, technology has become so important that no business is likely to survive without successfully undergoing the process of digital transformation.
Digital transformation and the fourth industrial revolution
The “Fourth Industrial Revolution” has as its essence in a digital revolution in which technology and computing are integrated with societies and therefore in industries. An era in which machines are capable of learning, making decisions and even collaborating with each other to achieve their goals. All these changes are based on a set of concepts, some that seem to be part of science fiction but are already part of our daily lives and that we must know.
What defines a digital transformation framework?
Although every industry has its own specific organization and structure, there are always common constants when it comes to talking about a digital transformation. This constant themes must be taken into consideration by all business and technology leaders facing the challenge of digital transformation:
- Digital integration
- Customer experience or user experience
- Workforce enablement
- Culture and leadership
The challenge of the new data and information management
Today we live in a world in which billions of bytes of information are generated every minute. This huge volume of information has become as valuable as it is unmanageable for companies seeking to optimize their products, reach their customers and ultimately develop their business. In this sense, data science is becoming more and more important in the day to day of the industries. We are mainly talking about mathematics applied to processes and systems that, through the use of the scientific method, help us to extract knowledge and achieve a better understanding of the data.
Data science and machine learning
The traditional programming processes and methodologies are reaching their limits because of the enormous amount of information generated in these days. The situation, far from being an insurmountable obstacle, has become an opportunity for the growth and development of new processes to deal with this unimaginable amount of information. Data science makes it easier to analyze information so that it is possible for the company to find opportunities that otherwise wouldn’t be possible to see. This is where automatic learning or machine learning arises.
This new scientific approach makes it possible to tackle the management, classification, tagging, and processing of the actual amount of data and information. Machine learning is, in the words of Cassie Kozyrkov, Head of Decision Intelligence at Google, “a tagger of things”: a system that is capable of learning how to define, classify and tag information so that from there people can manage it and make the best decisions. The simplest explanation hides behind it a tremendously complex underworld with enormous implications for the future of the industry.
The many faces of data science
Machine Learning is only one of the many disciplines in the world of data science. With the years, data science has grown to a field that englobes amongst others:
- Data analysis
- Predictive analysis
- Artificial intelligence
- Business intelligence
- Data mining
Undoubtedly, there are many more new technologies that will have an important role in digital transformation such as blockchain, augmented reality or cloud computing.
For a company to face the challenges of a digital transformation it will need to understand the role of every new technology. All of these fields of knowledge and their applications to the different business areas will be the core of our technological approach. We invite you to follow us in this exciting journey where we will explore and reflect on how technology will help companies to face the many challenges of the future. Join us and Go For More!