Do you want to be a data scientist but don’t have a programming background? It is not unnatural that you want to jump in your career or look for a more challenging role in your career. As a hot technology of today, data science or data analysis is the choice of many professionals. But if you are not from a programming background and deadened your spirit from becoming a data scientist, you will be happy to know that your fear is far from reality.

To start things from scratch, you must not give little inhibition and hesitance to create a wide gap between us and our dreams. So it is always good to put these fears to rest and look at things objectively.

Do you need to know programming to become a Data Scientist?

This is a common question that arises to any non-programmer’s mind before starting a data scientist career that how much programming language is required for data scientists? Another common question that pops up often is what the pre-requites to become a data scientist, or data analyst are? This is a vast topic. It could be a myth that data science is only for people with a programming mindset. However, it is partially true but not limited. Many great data scientists had started their careers without any previous background in programming. Let’s explore what’s really important to become a data scientist?

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What do you need to become a data scientist?

The lack of programming skills should not be the bottleneck for individuals from considering a career in data science. There has been apprehension for a long that to become a data scientist, he/she must be a great programmer. However, this thought process has a limitation. This is just like saying that to swim in the sea, you must be a fish. But the fact is several other creatures can swim and are not fish. The fact is to become a data scientist, you need a specific programming skillset, but any organization looking to hire a data scientist requires someone with a diverse skill set and not just programming.

To become a data scientist, this is not the matter that how much programming language is required for data scientist instead how much one understands basic programming and a certain comfort level with it. Basics of programming mean loops, functions, if-else, and programming logic. Being a good programmer is a highly preferred skill for a data scientist but not mandatory. 

Now come to the essential skillset that you must have to become a data scientist.

For non-IT experts to become data scientists or data analyst, even if you don’t have programming skills, you must have the following abilities:

· you should have a love for probability and statistics 

· love for numbers. 

· you should be comfortable enough to learn any new programming languages using the Internet’s resources. 

· Ability to identify a business problem

· Ability to work on the given dataset

· Data analyses capability from different perspectives

· build machine learning models to visualize and predict outcomes 

· weaves a story to convey the insights to the stakeholders. 

So, we can see that a data scientist’s job role involves mainly modeling skills, communication skills, business acumen, and analytical skills, all of which rank above the technical programming skills. The only essential and mandatory skill that you need to become a successful data scientist is the ability to analyze data and extract meaningful insights out of it. Also, for data science, two essential programming skills are R and Python, which you need to understand along with SQL queries.

What basic programming language required for data scientists

The programming skills required to depend on what area of analytics or data science you are likely to work on. For any help deciding on the ideal path within data science, better to talk with an experienced data scientist who can help you make the right decision. In most cases, multinational companies use SQL throughout their operations and adopt a data strategy requiring you to possess legacy skills such as SQL to manage databases. If you plan to take that data and perform analytics, modeling, and data visualization, consider learning Python or R to work with large datasets. In case you want to convert static visualizations into interactive ones by creating reports and online dashboards, having knowledge of HTML and JavaScript helps.

Non-programming skills that you need to acquire

Tools to learn

For non-programmers to become a data scientist, it is most essential to know some GUI-based tools like Microsoft excel, Rattle, Auto-Weka, or Tableau. These tools provide a user-friendly interface that helps anyone with basic knowledge of algorithms. Most of these GUI tools are available for free and let you analyze and present data through graphs, charts, and other special graphics. However, one need not possess excellent programming abilities to use these tools effectively.

Be a great storyteller.

Do you know that critical business decisions depend not only on data and other quantitative factors? You’re wrong. Even you need to draft the machine learning model or analytical model using programming; someone has to convey the outcomes to the stakeholders who neither understand the nitty-gritty of statistical models or programming languages nor understand the technical details. So, you need to explain it in a simple story format so that stakeholders can get the insights to persuade faster. Hence, you can become that person with excellent storytelling skills even if you lack programming skills.

Your domain knowledge matters

Are you someone who doesn’t have programming experience but in-depth domain knowledge in any of the fields like healthcare, insurance, e-commerce, retail, etc.? Then, indeed you are in demand in any organization for your domain knowledge. No degree of expert programming knowledge can beat the business acumen in a specific domain for a long time. Make the best use of your domain experience and skills.

Final verdict

The success mantra to land a top gig as a data scientist is “The More You Know, The Better It Is.”. Having programming knowledge is a plus, but organizations appreciate professionals who bring in a diverse skill set. A marketing manager with good business domain knowledge, an excellent grasp of math and numbers, statistical knowledge, and extraordinary marketing skills will definitely be preferred over a candidate with only specialized expert programming skills. So, if you are a non-programmer looking to pursue a data science career, there is no reason to be demotivated for not having programming knowledge. Better to develop a diverse set of skills mentioned above to become a successful data scientist