I was an English major in college and now I lead a data analytics team. Here are 3 ways I became a 'numbers person.'

• Overcompensating in one skill to make up for another is how I learned about data analytics.
• Hands-on data experience is a great way to break down the mental barrier of working with numbers.

I've always been a bit hacky to make up for some skills that never quite clicked with me.

I was an English major who somehow got through college barely reading any of my assigned reading. I was a bad reader, but a decent writer. I had trouble absorbing information in the classroom, but I could ace an interview to get internships and learn on the job. I can't whistle, but I can walk and chew gum at the same time. You get the idea.

Overcompensating in one skill to make up for another is how I starting learning about data analytics. I realized that when you're fresh out of ideas or don't know where to strategically turn, the data at your fingertips can lead the way and unlock a whole world of insights.

My favorite part of this "pivot" is that despite working with numbers all day, I genuinely use my English degree more than I ever thought I would. This background actually helped me compensate for my technical skill limitations. The critical thinking I learned in school and the writing skills I developed gave me a massive leg up on the fact that I was still learning about data and new ways to perform analyses.

Here are three tips that helped me become comfortable with data and transformed me into a "numbers person."

Become a Google sheets master

Google sheets, like Microsoft Excel, is an extremely powerful tool if you learn how to hone it. In my role at Insider, I've created dozens of tools and dashboards that save hundreds of people hours of work every day — and I did it in Sheets!

Getting hands-on with datasets in Sheets is an accessible way to gain experience in manipulating and calculating data. Even if your workplace uses Excel or a data visualization platform like Looker or Power BI, Sheets is an amazing primer for someone who is not familiar with working with large datasets and it will break down some math anxiety.

A resource I can't recommend enough is Ben Collins' Google Sheets course. There is a paid beginner course, but if you're all set on the basics then his Advanced Sheets course is free and is a great way to learn how to use more advanced Google Sheets capabilities and features. I frequently rewatch the lessons and I even use the course as part of my teams' onboarding.

Here are some of the most valuable Sheets functions (AKA formulas) and skills to learn:

• SUM - Calculates the total value from a set of values that are manually input or from a cell range.
• AVERAGE - Calculates the average of a set of values that are manually input or from a cell range.
• MEDIAN - Calculates the median of a set of values that are manually input or from a cell range. This is especially helpful when you want to exclude the high and low outliers.
• SUMIF - Calculates the total value from a cell range only including the values that match the conditional logic that you set.
• AVERAGEIF - Calculates the average value from a cell range only including the values that match the conditional logic that you set.
• COUNTIF - Counts the numbers of cells from a cell range only if it meets the criteria that you set.
• FILTER - Returns only the rows of a cell range that meets the criteria that you set.
• VLOOKUP or XLOOKUP - Allows you to search for a specific value in a range and returns the value of another column in the same row.
• IMPORTRANGE - Allows you to import data from one Google Sheet into another Google Sheet.
• IF statements - Returns your preset "true" or "false" value depending on if the statement meets the set conditions.
• Conditional formatting - Allows you to format the appearance of your data based on specific criteria about the data.
• Data validation - A feature that allows to constrain user input and creates a dropdown list of options.

My biggest tip for starting your Sheets journey is to assume that most of the manual calculations and filtering you're doing can actually be done for you by the computer — you just have to learn the right function.

Learn by doing

With any technical skill, one of the most efficient ways to learn is by trying! You might feel like you're not ready or don't know enough, but until you put your instincts to the test, you won't know what you don't know. I recommend picking a project and performing a "data analysis" which will illuminate where you have gaps.

When performing a data analysis:

• Decide on a question to answer: Starting with a clear question that you're setting out to answer is the best way to approach an analysis. An open-ended question often leads you down a rabbit hole.
• Determine how you'll measure the results: Is there a key indicator that will determine the answer? What datapoints will help you answer the question?
• Collect and clean up your data: Is there a public dataset you can use? Can you survey a group of friends? Can you collect some data online? Once you have your data, how do you want to organize it?
• Perform calculations on your data to draw conclusions: This is where Sheets can come in handy. Remember the purpose of this exercise is to familiarize yourself with working with data, so you don't need to have the most perfect calculations. Just play with different types of functions and slice your data different ways to see what it reveals.
• Interpret your data into clear insights and communicate them: What did the data tell you? What's the main takeaway you want to communicate? Is there a visual that helps get this learning across?

After you do the above...congrats, you're a data analyst: You've taken a question and used data to help draw a conclusion! You also went pretty deep on seeing how different calculations help you gain insight. You used math and you likely didn't cry!

Ask all the 'dumb' questions

As a self-learner, it's crucial to ask every question that comes to mind. The good news is we live in the age of the internet and there is a good chance that many others have asked your "dumb"question before. Our experiences are not unique and there are loads of forums online that prove that.

Because my mathematical background is limited, I can compensate with my research skills. It's really hard to learn if you're not asking questions. Knowing which questions to ask can often be the hardest part, so switch into the mindset of asking everything that comes into your head. Any roadblock you hit, stop and search for an answer. Importantly, you need to test what you find and understand why it will or won't work for you.

This process has really helped me realize that everyone has questions and it doesn't make you any less of an analyst to ask. In fact, asking the right questions is what makes a great analyst!