How to Succeed in Your First Analytics Role
This blog summarizes a webinar that I was a part of last week as one of three featured Tessellation analysts. We described our respective journeys into Analytics and how we have been able to learn, grow, and find success. We explained why and how we got into analytics, the qualifications we picked up along the way, and what advice we would give to anyone who wants to become a Data & Analytics professional.
Mitch comes from a medical background that includes having received a Master’s of Science in Public Health from Duke University. While studying epidemiology for his degree, he realized that academia/public health wasn’t the future career he wanted to pursue. However, epidemiology is highly analytical, and this aspect interested him—he realized that analytics moves the world forward.
Jake comes from a sports and sales background. He played semi-professional baseball, which is where he first fell in love with statistics. He held a position at Alteryx in the sales department to get his foot in the door with analytics. After years working at Alteryx and getting exposure to the industry, he eventually was able to go on and work in analytics himself.
I played golf for nearly twenty years, including Division 1 golf at Columbia University. After I graduated from college, I worked in sales, which I realized was not a path I wanted to continue. However, I had some experience with data cleaning in one of my sales roles; additionally, my golf career had exposed me to advanced sports analytics. I realized that this was something I was passionate about and wanted to pursue.
Mitch’s medical experience helped him develop analytical skills and thinking. On top of this, he demonstrated quick learning with online certifications in Python, R, Tableau and SQL. He also had a strong LinkedIn page and a portfolio on data visualizations on Tableau Public.
Jake had a strong LinkedIn profile and was even included as an Analytics Ambassador Leader in Onalytica’s report of the 2021 Top 100 “Who’s Who” in Data Science. He is also very active in the Alteryx Community and is Alteryx Core Certified.
Similarly to Mitch, I also received online certifications in Python, SQL and Tableau. I also had a strong Tableau Public Profile and made sure to fully revamp my LinkedIn page. This personal branding helped with job searching and showcased my technical skills.
Although our journeys into Data & Analytics might have been different, our qualifications do not differ much. We all had a strong LinkedIn profile, an expansive work portfolio and a proven ability with technical skills.
How to Build Technical Skills
There are many ways to build technical skills—you can get a tool certification like Jake with his Alteryx Core Certification, or you can get online certifications in different tools like Mitch and I did.
There are many resources for e-learning, but the best platform that I’ve come across is Data Coach. Data Coach is great for anyone looking to get started in Tableau, Alteryx, Power BI and Snowflake. Something that separates Data Coach from the rest is its capstone project structure—unlike other platforms that provide you with a dataset and specific question for your capstone project, Data Coach allows you to choose your own dataset and question. This allows you to flex your creative and problem-solving skills and has more practical applications for your data career.
There are also YouTube videos online on every tool listed above, including a Data Coach YouTube channel that has many helpful videos.
How to Build a Work Portfolio
Having a built-out Tableau public profile, GitHub page, and Alteryx community posts are all strong ways to show your skills and knowledge without having any work experience. Mitch and I both had Tableau Public profiles, while Jake had a strong presence in the Alteryx Community.
Many people have questions about where to start on a project or what to do it on. Simply grabbing a dataset, playing around with a tool and creating some analysis is a good start for any project.
Sites to find data for analysis include: data.world, Makeover Monday (tableau), Kaggle, Real World Fake Data, Reddit r/datasets, government websites, and plenty of others. There is no shortage of data out there to explore!
Contrary to how it may initially seem, it is not difficult to begin your journey into data and analytics. People in the field have many different backgrounds, and a typical technical background is not necessary. It is possible to build your own skills and work experience by learning online and doing projects on your own.
If you have any questions or want to chat about Data & Analytics, feel free to connect with me on LinkedIn. Make sure to also connect with Jake and Mitch as well. We are always willing to help people trying to make their way in the industry!
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