How to become a data analyst: Guide to Technical and Non Technical Skills

That is great. Let us start by explaining what data science is shall we?

Data science is a branch of science that employs scientific methods, systems, algorithms, and procedures to generate knowledge and useful information from data. The information gotten can be applied in many other fields such as medicine, engineering, and more. In short, data science is the science of data.

The person that practices data science is a data scientist.

Now you might be wondering, why is data science so important?

Simply put, the world is one big data bank. Due to the increase in the use of the internet in every part of the world, every person that uses a device generates a large amount of data. These data can be used to make several decisions to benefit people, businesses, and the world at large but how can we use data when we don’t understand it?  The short answer is, that we can’t. This is why data science is so important as it helps in processing and interpreting data.

What are the skills needed to become a successful data scientist?

You need 2 types of skills in data science. These are:

1. Technical skills
2. Non–technical skills

Technical skills

Technical skills are a collection of abilities or information that are utilized to carry out practical activities in data science such as:

• Multivariable calculus
• linear algebra
• Programming
• Predictive modeling
• Machine learning
• deep learning
• Data wrangling
• preparation
• Model deployment
• production
• Data visualization

 Non-technical skills

Non-technical skills are those that are not always directly related to your profession. They are interpersonal skills.

• Critical thinking
• Effective communication
• Proactive problem solving
• Curiosity
• Business sense
• team-work skills

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