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5 Data Science Trends to Watch in 2021

Here are 5 Data Science trends by DS Stream, to keep an eye on in 2021.

Warsaw, Poland, 02/25/2021 / DS Stream /

Data Science has been invariably very popular for years. We are talking about both the great interest of organizations, which recognize the enormous potential hidden in data, and programmers planning to develop their careers in the field of advanced data analysis. What changes should we expect in the coming months? What is the direction of Data Science?

Nowadays, analysts point to many different trends in the area of Data Science. The growing interest in data and how to use it in the business environment, as well as the dynamic development of new technologies and programming languages, only accelerate the progressive changes and, to a greater or lesser extent, revolutionize the way analytical teams function in organizations. What major changes can be expected in 2021?

1. Python Domination

Python, for several years, has been maintaining its position at the top of the most popular programming languages in the area of Data Science and is successively strengthening its position. Is there a chance that in the coming years, it will be at the top of the podium? There are many indicators that the occurrence of such a scenario is very likely. This is mainly due to the huge possibilities offered by Python, numerous free libraries, perfect for data analysis or building various models, as well as the relatively simple syntax, which directly translates into a short time of creating a working application. You can read more about Data Science and Big Data at DS Stream.

2. Augmented Analytics

The role of a data analyst is still unthreatened in many organizations, but there is no denying that analyses performed by humans are often based on wrong assumptions, habits, or biases. This leads to a more or less significant distortion of the results of the analysis and thus to taking not necessarily optimal business decisions. For this reason, among others, in the near future, we will observe the growing importance of extended analytics, based largely on machine learning and artificial intelligence.

3. Data Stories to Replace Dashboards

More widespread use of augmented analytics will also lead to changes in the way data is reported and visualized. It is very possible that the dashboards commonly used today will be replaced by automatically generated “data stories” presenting the various stages of the analysis and the conclusions drawn on its basis.

4. More Cloud than Ever Before

The cloud will become a permanent feature in organizations and will play an even more important role in the area of big data analytics. The cloud means high computing power and easier access to data, which translates into an improved end-user experience.

5. Focus on Data Governance

The growing use of data by organizations will equate to an increasing volume of data and, therefore, a greater need to exercise proper control over its access, confidentiality, integrity, and proper use.

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