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Congrats Graduates! What's Next?

“What’s next?” was the ultimate question I heard last year when I graduated from college. It is a daunting one. Now, some of you may have jobs lined up, plans to travel the world, or maybe you have no clue what is next. That is perfectly okay. We all want to rush into independence, rely upon ourselves, and make money; but I have learned this - now is the time to really find out about yourself and what you need in life.

Some of you may have come to this article because you are looking for what is next as a data analyst. How are you going to make your way in the world of analytics? Is it right for you? There are a lot of unknowns, but one of our CANA team members and Director of Analytics Capabilities, Walt DeGrange, is here to help. He broke down the life of typical day as an analyst to give you insights into what this job entails:

Research - 10%

Keeping up with the art of the possible is a required daily chore. New methods and technologies are being introduced daily. Assuming a software math solution implemented six months ago is still state-of-the-art is risking irrelevance.

Coding - 30%

This is the basic skill required for all analytics professionals. As important as the carpenter's tools, coding in various languages such as R, Python, C++, and SAS allows the analytics professional to manipulate and gain insight from data sets.

Communication - 25%

Communicating with collaborators, clients, project leads, and technical experts is critical to ensure that deliverables are on time and fulfill the requirement.

Marketing - 15%

Everyone needs to sell. Even the coder that never presents to a client must convince their project lead that their methodology works. This is a very important skill for analytics professionals since many models use math that is not easily understood or explained. These "black box" solutions require a higher level of convincing.

Project Management - 10%

Keeping analytics projects on track is not like managing a construction project. There are many analysis areas that require familiarization with the data before building a model. Many aspects of model building are more of an art form than a science and thus the time to complete may have a large variation from project to project. One must consider this in the planning and execution of these projects.

Breaks - 10%

Everyone needs a break, and this is especially true if your job keeps you in front of a computer screen. Walking, running, and cycling gives you time and space to think about challenges. Sometimes your subconscious mind needs this distraction to develop solutions. Plus, the physical exercise is just good for you.

Walt sums it up this way: “Of course, this is just a sample day. Why I love analytics is that I can apply the techniques across many industries and solve a multitude of challenges. This results in schedule variation every day.”

I know each of you will enjoy the challenges and excitement of your chosen field, whether in data analytics or elsewhere. You have earned your college degree, and we here at CANA applaud you!


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