You’ve done it! You’re a data analyst and are beginning your journey as a professional; however, it’s not all what you expected and there are some hiccups early on, but you’re moving forward with your head held high. As you gain more experience, however, you start to realize a few patterns begin repeating themselves more and more, leading you to wonder: is this what every data analyst experiences? The answer is yes–data analysts around the world, no matter their location, specific role, or experience level, are experiencing some of the same things.
A Day in the Life of a Data Analyst
Before we dive right into things only data analysts will understand, let’s cover what data analysts tend to do in their day-to-day, highlighting what makes the role so crucial:
Meeting with teammates to explain data: meetings make up a lot of what data analysts do, explaining what their plans for using data are and then sharing the results with the rest of the team after the analysis has taken place.
Gathering data: the first step of data analysis is clear: you need to have data to work with! This means that you must have a clear plan for how you’ll gather your data and what kind of data will be of use to you.
Cleaning data: with your data collected, you need to make sure it’s ready for analysis, cleaning it and making sure it’s free of errors, missing inputs, or outliers.
Processing data: it’s time to see what your data shows you, analyzing it to identify trends and patterns.
Data analysts also produce reports that put their findings into writing so that everyone else, especially stakeholders and higher-ups, can understand what their findings actually mean for the company.
Things Only Data Analysts Will Understand
With a clear understanding of the day-to-day of data analysts, let’s review the things that only data analysts can understand, focusing on those frequent frustrations that arise from those who aren’t that familiar with data and the role of data analysts.
When someone says: “Doesn’t the computer analyze the data for you?”
We’ve all been there: you’ve studied hard and learned what you need to know to start your data career and some uncle or friend of a friend thinks you’re just there to push buttons and let the computer do its magic. While this can be quite frustrating, you know the truth: software and algorithms are incredibly useful when it comes to analyzing large amounts of data, but your role as an analyst and someone who knows how to manage and use this system is incredibly valuable.
Our tip: this is incredibly frustrating, especially after you’ve worked so hard to get where you are. So instead of letting it get to you, think about it like this: what you do is so amazing that they think only a computer can do it. You’re basically a superhero!
When you find discrepancies in the data after you complete the analysis
You’ve done it: you’ve completed an analysis of a data set and are eager to bring your findings to stakeholders to share what you’ve learned. However, right when you think you’re finished, you realize that there’s an error in the data set; be it unclean data, missing variables, or clear bias, you’re back to square one and feel quite dejected.
Our tip: this happens to absolutely everyone and even in fields outside of data analytics, so don’t take it personally or as a reflection of your abilities. Instead, correct the mistake and try to figure out what went wrong so that in the future, you’re able to avoid the same error again.
When someone asks if your job is just using Excel
Spreadsheets, spreadsheets, and more spreadsheets: sometimes it may truly feel like your job is just Excel, spending hours entering and checking data sets. But you know that spreadsheets are just a tool to help you organize yourself and should be treated as just that–nothing more!
Our tip: next time someone asks you this, inform them of all the other tools you use in your job to organize and analyze your data–you’ll stop them right in their tracks and make sure they don’t ask that again!
When someone is surprised you know programming languages
Gasp! You’re skilled in something outside of simple data? Little do they know: programming language knowledge is completely normal in data analytics and the majority of data science roles require some programming language knowledge; even as computers are getting better at automated coding, many data professionals still prefer being able to check the code themselves and ensure everything is working correctly.
Our tip: leave the haters in your wake! You’re a well-rounded professional who can master a wide range of skills and that’s why the tech world is such a perfect fit for you. Keep expanding your repertoire and don’t listen to what the others have to say–you know what’s best for you and your career.
When someone thinks presenting the data is the easiest part of the job
We get it: the data analysis part of data analytics should be the toughest part, right? That’s what a lot of people think and that’s totally fair. But when it comes down to it, verbalizing your discoveries and findings to other team members or stakeholders can be quite the challenge: you need to put it into words that non-data professionals will understand, while still maintaining the importance of what you’ve discovered.
Our tip: use charts and other visuals to help get your point across, letting the image of your findings help communicate the importance of your findings. If you’re still having trouble, try practicing with a non-data professional coworker before presentations so that they can help pinpoint problem points.
Working as a data analyst is incredible–but you already know that! If you are looking to begin your career in data analytics or finetine some of your data skills, you’re in the right place. Ironhack’s Data Analytics Bootcamp is designed with the help of data experts, focusing on teaching you the latest trends in data science and helping you land your next job in data.
If you’re ready to start your data journey, we can’t wait to see you in class!