01 Oct How to switch to a career in data analysis

Transitioning or switching to a career in data analysis is not a piece of cake, especially if your current career path is non-technical. It is a road paved with many obstacles and you can get overwhelmed and frustrated somewhere along the line. In this blog post, I’m going to discuss a few things that will help you to switch easily to a career in data analysis.

I remember when I wanted to switch careers too. I had a long list of courses to take on several learning platforms. In the end, I became overwhelmed and had to retrace many steps back to do it the right way. So, it is completely okay that you are looking online for help on how to switch to a career in data analysis.

Note: This is not a life hack. They are just tips that will go a long way in easing your career transition.

Step 1: Is transitioning necessary?

As much as the world is now data-inclined, a career in data analysis is really not for everybody. Before transitioning, be sure to ask yourself if this switch is necessary. Do you really want to do it? If you are only transitioning because everyone is doing it, then you might not be able to push through when the challenges come.

Step 2: Research your position of interest.

There are many job positions in data analysis with different sets of required skills. While the title of a data analyst is the most popular one, and most likely the first one you thought of, there are other options. You can be a database administrator, a BI analyst, an IT systems analyst, a healthcare analyst, an operations analyst, etc. Each of these job positions has their required skill sets. Think about the job position you are interested in, and find out the necessary skill sets. Research industries that will require such services and be sure to check how rewarding it is.

Step 3: Develop your skills.

There are certain skills that are required of almost every data analyst. These skill sets are important when switching to a career in data analysis, and they include:

• Creative and Analytical thinking: It is critically important to be able to think through problems with a curious and creative point of view. I mean, how can you properly analyze data without good analytical skills?
• Data visualization: This is an extremely important skill for every data analyst. There are tools specifically built for data visualization, and the best way to fully equip yourself with this skill is to master these tools. A good example is Tableau. Being an expert in Tableau takes your skill level as a data analyst from 0 to 100 real quick. It also increases your chances of getting a job fast. There are many Tableau training programs but I will recommend Cndro’s Tableau training because it focuses on practicality and prepare you for actual on-the-job challenges.
• Programming languages: One of the most essential skills to effectively switch to a career in data analysis is the ability to read and write in code. Today’s most in-demand analytical languages are R and Python
• Advanced Microsoft Excel:
• SQL Databases: SQL databases are relational databases with structured data. Data is stored in tables and a data analyst pulls information from different tables to perform analysis. The ability to do this effectively will further ease your transitioning
• Data Cleaning: When data isn’t neatly stored in a database, data analysts must use other tools to gather unstructured data. Once they have enough data, they clean using programming.

There are many other skills, but their requirement levels can vary depending on the job position.

Step 4: Create a Portfolio

While switching to a career in data analysis, it is important to create a portfolio. Employers want to see concrete evidence of the things you can do, so start building a portfolio the moment you begin your learning process. As you develop your skills, update your portfolio. Not sure where to start? You can create a GitHub account, or sign up on Kaggle to have access to many open projects that you can practicalize with. These projects will strengthen your portfolio.

Step 5: Build a network.

It doesn’t matter if you love it or hate it, networking is important if you want to take that giant leap and switch to a career in data analysis. There are different ways to expand your network without going to networking events. You can start by getting the word out about your interest in data analysis to family, friends, and anyone who cares to listen. Post about it on LinkedIn, and connect with people in your field of interest (professionals and amateurs). You can find like-minded people on platforms like Quora and reach out to them for connections, advice, etc. Building and expanding your network will completely ease your transition process to a career in data analysis.

Transitioning to data analysis

There is no magical process to this, transitioning careers don’t happen overnight, especially to data analysis. You have to be willing to put in the work and develop yourself. If you have started your transitioning process or you are just about to, you can ask questions in the comments section for more help.