A Day in the Life of a Data Analyst By: Nour Abi-Nakhoul December 10, 2020 Marie Gallagher is a data analyst within the Integration, Analytics & Data Science team at La Presse. She leverages data to support daily business decisions, collaborate with business partners, to extract insights and develop new initiatives that guide strategies. Marie is also the instructor of the Introduction to Data Analytics course at Lighthouse Labs. She is committed to sharing her passion for data with others. Data science is a field of study that’s applicable to so many different industries. From HR to agriculture, supply chain management to the restaurant industry, there are innumerable places and people that can and do benefit from the use of data. Because of this variability, there’s no one way a career in data looks. A data analyst can spend their days compiling biological data for scientific research, or cleaning up information for a furniture company. A lot of people might have difficulty imagining what the day-to-day life of a data analyst is like — who are these number-crunching professionals that walk among us, and how do they spend their days? To help you better envision what a career in data could potentially look like, we spoke to one data analyst about her career trajectory and day-to-day life. Marie Gallagher teaches the Introduction to Data Analytics course here at Lighthouse Labs. She also works as a data analyst over at La Presse, one of Quebec’s big newspapers. Read on to learn about how Marie got involved in data, what her life looks like now, and what advice she has for aspiring analysts. Becoming a Data Analyst Marie’s career in data analytics started in Montreal. After graduating with a master’s degree in business intelligence, she began to work as a research analyst. Later, this experience segued into a position as a data analyst with Cirque du Soleil, where she created and began to work with a data science team. In that position, she used both internal and external data to build solutions for a number of different purposes, from marketing and sales to social media and CRM. But what attracted Marie to data analytics in the first place? “I really like using numbers and statistics to better understand things, hence my background in finance. I like to use solid facts and numbers to support my own decisions as well as business decisions.” She happened upon the study of business intelligence through a friend, and so began her career. A Typical Day as a Data Analyst In her current role, Marie works as a data analyst for La Presse, a digital newspaper in Quebec. There, she does a variety of different things. “As a data analyst, every day is variable,” Marie says, “I typically spend my day working on bigger projects that take me a few months to complete, interspersed with other smaller requests from colleagues.” In her role, she analyzes different data sources to support these varied initiatives. In terms of the nitty gritty of what she does: she’ll create visualizations, help support new strategies, monitor certain trends, and keep track of the marketing industry and different sales initiatives. She’ll also use her programming skills to automate certain tasks, something that Python is great for. Python is taught in our data science courses, and that’s what Marie uses to run her analyses. She also makes use of a variety of other technologies: Tableau for visualizations, Excel for exploring data, and SQL syntax for working within the cloud. Data Analyst Challenges and Difficulties As with any job, a career in data analytics brings with it its own unique challenges. For Marie, data validation is one of the biggest challenges. “I need to constantly validate that I’m working with good data, and that what I’m looking for are the right variables,” Marie explains. “Sometimes this can be difficult to validate.” Marie goes on to explain that with experience, this challenge becomes easier to manage. The more you play around with data, the more expertise you gain — which is great for knowing when data is good or not. Big Data is one of data science’s buzzwords from the last few years, referring to the huge datasets that are increasingly produced by our high-tech society. But as Marie explains, though working with Big Data can be beneficial, it’s not without its drawbacks. “Working with Big Data can be really costly, so it depends on the budget that’s available. It necessitates finding ways to aggregate the data without it costing too much to store it.” What Skills do Data Analysts Need? Marie gave us an idea of some of the skills that a data analyst needs to have to succeed in their career. Though a proficiency with numbers and an interest in manipulating information is important, data analysts actually need to use a variety of different skill sets. Marie named the trinity of skills a good data analyst should have: analytical skills, technical skills, and communication skills. Analytical skills are important for a data analyst because they need to be able to make analyses and interpret results. Technical skills are also very important, because a data analyst will constantly be acquiring and cleaning data. What may be surprising is that communication skills are also very valuable for a data analyst. As a data analyst, you’ll need to be able to effectively communicate with others “both to understand the context of their situation and what they need, as well as to present information to them,” says Marie. Why Become a Data Analyst? Marie enjoys her role as a data analyst, and the field of data science might be exciting for you as well. Data analytics can be a really valuable industry to start a career in. “Data analysis is relatively new, so there’s a lot of demand for data analysts,” says Marie. “Data analytics can also be incorporated into every industry and every department.” The reality of today’s workforce is that many companies want to become more data-driven, but they don’t necessarily know how to make that shift. That’s where data analysts can come in. Data analysts are there to help these companies develop data-driven ways to make smarter decisions. Want to start your own career in data science? Check out our Data Science Bootcamp program.