Making every task count towards your data experience
I have been striving for a couple of years to land myself a role as a data scientist. It is a scope that I always look forward to land on ever since I took on the decision to transit from accounting to data analytics. However, I may not have the luck nor the competency to land myself in a data scientist role. Nonetheless, it does not mean that the data tasks you had will not be relevant towards your data experience.
Every data task adds value to your skill set
I was being assigned to do data cleaning and pre-processing when I worked for a start up that specializes in aggregating data from different sources. The process was in fact very manual and tedious, involving laborious effort to get things done from end to end. In my point of view, it is not very value-adding because it does not involved a lot of thinking.
The process includes manually typing in data into the data system, converting data from one format to another. For many occasions, we need the intervention of human to correct the errors in the system. This may seem like a repetitive and boring task but it actually gives you the perspective that data in its raw form, is very very dirty.
Seek to improve your scope of work
It is very common that your actual scope may not be the same as what being described in the job description. You could be doing things out of your current scope or you may not even touch the items as stated in the job description. It might be natural to feel frustrated as it is not really the job you want to do. However, in reality, most of us do not get to choose what we want to do. Even when you start your own business, it is likely that in the beginning that things will not go the way you expected.
Rather than being upset about the situation, we can always take this as an opportunity to explore the innovative side of us. One example is automation of your current repetitive assignments. During the course of my work, I have a lot of reports and data entry tasks that I have to update on a regular basis. Each task takes quite a bit of time and this adds up to consuming most of my working hours, thereby not adding value to my work. It will be a skill upgrade when you are able to automate and increase productivity for the company.
Learn more things out of your scope
This is a personal preference but I do enjoy learning things out of my own scope. For example, I am a data analyst but I try to understand data engineering because it is going to help me understand how to design data pipelines which can be useful for new data projects.
Likewise, I try to learn other programming languages even though my strength is python and SQL. This challenges my adaptability to pick up new skills as this space is continuously evolving. These are things that I do for every role that I was involved in, always seeking to expand my horizon. Eventually, this is going to be very useful because you are able to apply what you learn if you were to move to other roles.
Every experience is different
Even though you may have a common title when you move across industries such as data analyst, financial analyst or engineer, each role you take on is different in nature. From my experience, it is the type of data and the domain knowledge. I have touched on finance, credit risk and customer analytics during the course of my analytics journey. Though the stints may not be long but it adds value to your overall profile.
What else you can do?
There are definitely some situations when the work is pretty mundane or repetitive that you can’t seem to add value to your career profile. You can always try your best to find new courses to build your own portfolio. This is about pushing yourself out of your own comfort zone. You need not be upgrading yourself all the time but by being active will keep your learning gears moving. This is especially true if you have graduated from school for a long time. You will tend to have a strong inertia to get things started. Learning is a continuous journey and we should keep striving to get better.
In conclusion, continue to accumulate your experience in data and eventually you will be able to reap the fruits of your efforts!
I have a website known as https://goingmeraki.com which I have published other posts including tutorials. You may visit it to know more about my journey towards becoming a data analyst. Please visit @goingmeraki on instagram for short posts too!
