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As the world becomes increasingly data-driven, individuals from diverse fields are turning their attention towards data science. Lisa, a social scientist from Berlin, Germany, is one such individual. Dataquest became her platform of choice to facilitate this transformation, setting her on a path from social science to data engineering.
Before discovering Dataquest, Lisa was deeply involved in voluntary work with CorrelAid, a Data4Good community of over 2400 data enthusiasts. This experience led her to an unexpected opportunity. She explains, “I got the job through my voluntary work with CorrelAid. I had done a project with an NGO three years before and when they heard that I was looking for a job they reached out to me.” It was this direction that piqued her interest in data engineering.
Lisa chose data engineering due to its practical approach and focus on fundamental computer science concepts. “I chose the Data Engineering Path: I have not formally studied Computer Science so it’s interesting to me to learn about some of the basic concepts like how information is stored in computers or the big O notation,” says Lisa.
This path offered more than just data analysis; it provided an in-depth understanding of the mechanics operating behind the scenes, aligning perfectly with her curiosity and career aspirations. Further enhancing her learning experience was Dataquest’s practical focus and the platform’s seamless, setup-free environment, which appealed to Lisa’s desire for a streamlined educational journey.
Lisa’s journey with Dataquest was not without its challenges. She struggled with consistency, finding it difficult to maintain a regular learning schedule due to her busy lifestyle. However, she discovered that the projects at the end of each section were invaluable in reinforcing her learning and enabling her to apply her newfound skills. “I liked that you also have projects at the end of a section. They are very time-consuming but that’s also a really good way to apply what I learned theoretically and find out how to overcome all the little things that come along in real life,” she states.
Dataquest played a critical role in shaping Lisa’s career direction. She appreciates the platform for helping her gain essential skills, which in turn boosted her confidence. Lisa explains, “It helped me to decide which direction I want my career to take because I could gain skills in one area over a longer time period and then feel confident to take on tasks in that area in my job.”
Lisa’s advice to learners emphasizes the importance of consistency and the power of showing up. She advises, “Decide on a path, set a specific time and place where you want to learn each day and then show up. Over time you will get better by ‘just’ showing up. But don’t be fooled, even carving out ten minutes a day is a lot tougher than you might think.”
Lisa’s journey from social science to data engineering has been transformative. Through Dataquest, she gained a deep appreciation for the tools she now uses. She concludes, “Even though I now use pandas, I have learned and went through the painful way to read in CSV files with Dataquest and it makes me appreciate pandas so much more. But I also know how I could do it, in case I cannot use pandas.” This underscores the practical, real-world value of the skills Lisa gained with Dataquest, propelling her into her new role as a data engineer.
