5 Essential Skills For Anyone Looking To Become A Data Scientist In 2020

"Data science is his sexiest job of the 21st century." These are the words of the Harvard Business Review. We all know that what oil did in the 20th century, data will do this year. There is a huge opportunity right now, and this is just the beginning.

However, most people think of data science as just an academic discipline. No, it's not. It's many skills rolled into one. Even programmers need to be familiar with coding, structures, algorithms, and computer networks. So why aren't these scientists? Data science is one of the fields that will continue to grow in popularity.
What is data science? 
I won't go into too much detail, but here's a basic overview:

Data is the combination of different tools, sources, and statistics to get the job done. It starts with raw data extraction and ends with targeted filtering. It is one of the most powerful tools that helps businesses make informed decisions and solve various problems. 
5 super skills for data scientists

Here are five essential skills that aspiring data scientists should know as they prepare for new technological changes.
Statistics and probability

Data science uses various algorithms to extract raw data. Statistics and probability help make inferences for further analysis. With sufficient knowledge, you can explore and understand them more deeply, identify relationships between variables, determine different patterns, detect anomalies, make decisions, build models, and identify future trends. can be predicted. programming and software

It's no surprise that this "science" is essentially technical and programmatic in nature. Therefore, it is especially important to know some technical skills, coding, and programming languages such as Python, R programming, SQL, Java, and TensorFlow. Knowing even a little bit can be very helpful. Most of these languages are useful for problem solving and help transform raw data into actionable insights.
database management

Database management consists of programs that allow you to edit, index, and manipulate databases. It allows you to define and manage all your databases, manipulate, format, and modify their structures, as well as test and verify them. For data scientists, it is essential to be able to manage databases from top to bottom.
Data processing and visualization

Once the data is extracted and organized, the next step is to analyze it. It's important to understand how features work and what they can do for your business. Wrangling is useful for processing further analysis, mapping and combining related fields, and cleaning up afterwards. Once this is represented, the next step is data visualization. You need to learn to express it in graphic form and convey what it says. Provides a comprehensive view and helps in decision-making. Therefore, it is one of the most important skills for us. cloud computing

This often involves the use of cloud computing products and services to make resources more accessible to professionals. All your data is stored in the cloud, so it's important to understand cloud computing. Provides access to a variety of databases, frameworks, and other operational tools. This field interacts a lot with data volume, data size, availability, and other factors, making it a must-have skill for anyone interested in this field.

My recommendation is to start with programming and then learn statistics and probability. These two are super important. You may have someone else do your database management for you, but you'll need to know about that as well. Also, since this niche is the future, I recommend learning about cloud computing.

I think the list is complete, so start learning.

Article Source: https://boostarticles.com

Join Us: https://boostarticles.com/signup