There are a lot of people that want to transition into a data career, why? Because data rocks!!
Data is a great field to be in right now, and I’m not only saying this because it appears to be the hot new trend or because I am part of the data community. I don’t know if you have noticed this or not, but data is EVERYWHERE!!
We have reached the point where our television recommends shows and our kitchen appliances tell us when we are out of milk. This is why I scratch my head when some people don’t believe they can transition into the data field if they are coming from somewhere else. A lot of folks think you have to learn a bunch of new skills before even thinking about the move.
Have you ever heard of the term, transferable skills? Let’s look into that 👀
In the rawest form, transferable skills are skills that you take with you from one job to another. These can be both hard skills and soft skills, both which are needed as a data professional. Let take a look at some transferable soft skills that are critical for data professionals:
At first, this may just look like some random words pulled from a resume but I assure you that these skills exist in EVERY job and in EVERY industry (not just in data).
For fun, let’s take a look at an example: The Hairdresser
This is my go-to example for transferable skills in the data field because pretty much every person can relate. Let me set the stage 🎭
Susan is in need of a haircut and books an appointment with Daisy. Susan thinks she knows what she wants and explains to Daisy, in detail, that she would like her hair cut short like Jamie Lee Curtis and dyed jet black like Krysten Ritter. Because Daisy was using her attention to detail skills, she notices that Susan has fine hair and remembered that she mentioned earlier she likes to try out new hair colors often. Using her communication skills, Daisy summarizes Susan’s requirements but then suggests a different cut and color while explaining that they would work better with her fine hair type and desire to change colors in the near future (one could say this is part of problem solving). Since Daisy is a curious cat, she explores different options with Susan and they are able to both agree and adapt to the new approach.
This is a scenario that happens very often for data professionals when working on projects. Here, Susan is the Stakeholder and Daisy is the Data Professional. Susan presents the requirements for a new project, and Daisy makes sure that the requirements are possible and will achieve the desired results. If Daisy ever wanted to work as a Data Professional, she totally has the skills! 🤓
UPDATE: I have received some good feedback on this article, people seem to like my Hairdresser example so let's keep the fun going and add another
This one may not be AS relatable to the Hairdresser but I love tattoos, getting tattoos, and currently have some fresh ink 😻 So let's talk about: The Tattoo Artist
Much like with data projects, the tattooing process starts at the end. Whether it is a well thought-out design or something random you thought of that day, you need to describe the desired end result to the artist. While describing the tattoo, the artist pays super close attention to detail while also presenting a bit of curiosity. In my experience, the artist always asks a lot of questions including the inspiration for the tattoo, the location of the piece on the body, the size, the colors that are going to be involved, and even the last time the customer has eaten. All of these follow-up questions are coming from a preemptive problem solving mindset. At this stage, it is imperative to have strong communication skills to ensure that both parties are on the same page. Once this is set, the work can begin! While performing the work, the artist continues to use communication skills to make sure the customer is comfortable and healthy. At any time a need could arise causing a switch to problem solving mode, whether that be the alignment of the art is off, the color is wrong, or maybe the customer needs some orange juice to boost their blood sugar. This kind of stuff happens all the time and any tattoo artist will be ready to adapt to the situation. After the work is complete, curiosity kicks back in as they often ask to be kept in the loop and see the piece after it has healed.
Again, this situation is incredibly common to working on a data project for a stakeholder. Here, the customer getting the tattoo is the stakeholder and the Tattoo Artist is the data professional. Stakeholders need to be able to explain their desired end product and the data professional is responsible for delivering that product while ensuring the experience goes smoothly.
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