Top 5 Data Science Skills that Data Professionals and Leaders Must Know

Multiple essential data science skills are in high demand from data professionals in 2022

Data science encompasses data analytics, data mining, artificial intelligence, and several other related disciplines. The value of the structured and unstructured bulk of data is the most important. However, outside of the technical curriculum, there are data science skills that will transcend disciplines. Practicing and developing these skills is essential to becoming data professionals and leaders. In this article, we have will go through some of the most desired skills that industry experts wish to see in data professionals and leaders in 2022.

Analytics and Modeling

A skilled data science professional is expected to possess high proficiency in this area. Based on the foundation of critical thinking and communication, leaders have to learn to analyze data, run tests, and create models to gather new insights and predict possible outcomes.

Programming

Obtaining programming skills is essential in data science. Most businesses will expect their leaders to know basic programming skills in Python and R, as well as other necessary programming languages. Object-oriented programming, basic syntax, and functions, flow control statements, as well as knowledge about language libraries, are essential skills for business leaders to possess.

Data Visualization

Data visualization is the key to effectively communicating messages and getting buy-in for proposed solutions. Understanding how to break down complex data into smaller pieces and using a variety of visual aids is a skill that data science professionals should be proficient in. They should be able to create charts, graphs, and other such things to help enable other data science employees to find out errors while presenting and rectify them.

Leverage Self-Service Analytics Platforms

C-suite leaders should not only gain insights on utilizing such advanced technologies but also understand the challenges involved in utilizing them. Self-service analytics platforms can help data professionals process the explore the data and also effectively communicate the results with the less-technical employees, enabling efficiency across all business platforms.

Maths and Statistics

Coding, maths, and statistics play a critical role in data science. Data scientists deal with mathematical and statistical models and must be able to apply and expand on them. Besides, having a strong knowledge of statistics will enable the professionals to think critically about the value of various data and the types of questions it can or cannot answer.