Companies around the world, of all sizes and sectors, have long noticed the importance and positive impact that the implementation of Data Science solutions has on the constant and healthy growth of their businesses.
And there is concrete data proving that the value of Data Science for companies will only increase over time.
A report released by Allied Market Research indicated that the Data Science solutions market had a global value of 4.7 billion dollars in 2020. The estimate indicates that this market should reach 79.7 billion dollars by 2030.
Data Science , like everything that involves technology, innovation and business, is something that is constantly evolving. Staying on top of the changes and trends that surround it can guarantee relevant competitive advantages for your business.
Discover now 4 Data Science trends for the coming years.
1 – Data Science beyond technology companies
Nowadays, even though Data Science applications are much more widespread, the percentage of visitors who rated is that the organizations that use them are still very much linked to sectors such as consumer technology, e-commerce and marketing. But this is a reality that should change in the near future.
Little by little, important sectors for the global economy such as health, agriculture and different industries are opening their eyes to the opportunities that Data Science solutions represent.
And, as the adoption of Data Science application technologies expands, the entire production chain on the planet tends to benefit. This is because, in addition to significant increases in terms of innovation and efficiency, Data Science can be the gateway for people from other areas to learn about and become interested in the subject.
2 – Decision making as a science
Nowadays, even with all the writing with artificial intelligence – yes or no? and ease of access to information like never before, there are still those who try to guide companies based on guesswork or feelings .
But the tendency is that, over time, this type of management will become something relegated to the past.
Data Science , as you may already know, is the practice of making information gained from data useful and actionable. In other words: less room for guesswork and unfounded assumptions.
3 – Combining Big Data and Internet of Things (IoT)
As we have already discussed , the Internet of Things (or IoT ) allows common objects in our daily lives to be mobile lead to the internet, receiving and sharing data.
The result of this is a window of opportunity represented by the existence of more accurate and up-to-date data, which is perfect for Data Science solutions .
4 – Increasing presence of hyperautomation
Hyperautomation , as the name suggests, is a more advanced stage of automation .
In short, we can say that hyperautomation combines different technologies and concepts (such as Artificial Intelligence , RPA and Machine Learning ) to automate all tasks that can be automated within an organization.