If you still get anxious thinking about math quizzes and stay far away from numbers-heavy fields, then data analytics might seem way out of your comfort zone. But here’s the thing your math teachers probably never told you: You don’t have to be a math whiz or a “numbers person” to work with data.

Data analytics is all about the process of collecting and analyzing data for insights. A Data Analyst often works with numerical data and stats, but that doesn’t mean they’re doing complicated arithmetic in their head. “In fact, you’ll come to find that a lot of data science is situating numbers in their context,” explains Michelle McSweeney, Codecademy’s Data Science Domain Manager. A Business Intelligence (BI) Data Analyst, for example, is someone who uses statistics and analytics to write reports and build dashboards that help organizations turn data into actionable insights.

In other words, a Data Analyst’s job is to figure out the story behind the numbers, and then use those numbers to answer questions.

BI Data Analysts have to be able to interpret and contextualize numbers so that a wide range of audiences and stakeholders can understand what they mean. This requires a high level of data literacy — a term which may sound intimidating, but just refers to an ability to read, understand, and leverage data. “Numbers without a story don’t tell us much,” Michelle says. “So if you consider yourself a ‘words person,’ you are probably in the right place, because the best analysts turn numbers into insights and stories.”

Think you may want to work with data? The good news is that nearly every industry uses data to deliver business insights and inform decisions. And if you want to get started right away, Codecademy’s new BI Data Analyst Career Path is the quickest (and lowest code!) route to a career in data analytics. You’ll dive into the types and quality of data, and why human oversight and critical consideration is essential in the world of data. Plus, we’ll teach you how to use the technical tools and programming languages that BI Data Analysts use. By the end, you’ll be ready for an entry-level job in the field.

Most importantly, the BI Data Analyst Career Path is made for those of us who are not “numbers people,” and we’ll guide you through everything you need to know in a practical, data-first way, Michelle says.

The technical tools BI Data Analysts use

While BI Data Analysts may not be doing math on the regular, they do need to understand some programming in order to work efficiently with data. Here are the various programming languages and technical tools that you’ll learn to use in the BI Data Analyst Career Path.  

SQL

SQL is a programming language that’s designed for managing and querying data stored in relational databases. SQL is often recommended to coding beginners because it has a very readable, English-like syntax. Even newbie programmers who’ve never written code could probably tell what a snippet of SQL code does just by reading it.

For example, this is some SQL code for a movie database that you’ll work with in this Career Path:

SELECT *
FROM movies
WHERE year BETWEEN 1980 AND 1990;

In the BI Data Analyst Career Path, you’ll learn how to use SQL to query and manipulate data. Don’t stress if you’ve never taken a SQL course before — our path is beginner-friendly, and we’ll cover everything from the fundamentals of the language to advanced SQL techniques that are used to solve business problems.

Python

Python is a wildly popular data science programming language with a concise and intuitive syntax. The cool thing about Python is that there are tons of libraries and built-in functions that enable you to write code quickly and easily. In Codecademy’s BI Data Analyst Career Path, you’ll use data science tools like Python Pandas, seaborn, and MatPlotLib to manipulate data and create compelling data visualizations.

Be sure to check out all of Codecademy’s Python courses to see what else you can do with this versatile programming language.  

Excel

The spreadsheet software Microsoft Excel is used to store, display, and analyze data. There are lots of useful built-in Excel functions that allow you to complete basic computations with numerical data, like finding averages, sums, or maximum and minimum values. In the BI Data Analyst Career Path you’ll learn the basics of handling, analyzing, and visualizing data in Excel, plus work on data analysis projects using real-world datasets.

If you’re just looking to get better at using Excel, you can take the free Codecademy course Learn Microsoft Excel for Data Analysis to brush up on Excel’s filtering tools and formulas that are used in data analysis.

Tableau

Tableau is the go-to visual analytics platform in business intelligence. The user-friendly application enables you to build attractive, interactive visualizations and dashboards that tell a story with data. We’ll teach you how to use Tableau to import, manage, and visualize data in the BI Data Analyst Career Path. You can also check out the free course Learn Tableau for Data Visualization, to get more practice building Tableau dashboards.

Get started becoming a BI Data Analyst

To reiterate: You don’t need to be good at math in order to become a BI Data Analyst. However, there are some important data-specific skills you should have under your belt, like knowing how to get around a dataset, assess the quality and completeness of data, and join data together, Michelle says.

A good BI Data Analyst is someone who’s curious and open to asking questions about data and exploring what the numbers in a dataset really mean, Michelle says. “You might be surprised how much of your job will be just cleaning, joining, and exploring data to discover the most interesting bits,” she says.

Think you could have a career as a BI Data Analyst? Jump in right now and start the BI Data Analyst Career Path — it’s the quickest way to launch a rewarding and lucrative career in data analytics.

One last thing: While you’ll be writing code in the BI Data Analyst Career Path, the lessons are designed for beginners, so truly anyone interested in becoming a data professional can take it. By the end of this path, you’ll understand how and when to use industry-standard data analytics tools like Python, SQL, Tableau, and Microsoft Excel to answer business questions with data. You’ll even get to complete projects that you can use in a portfolio when it comes time to apply for jobs.

As you work through the BI Data Analyst Career Path, be sure to connect with your fellow learners and job seekers through Codecademy forums. Who knows? Maybe you’ll discover you’re a “numbers person” after all.