The Sexiest Job of The 21st Century
Facebook Users Are More Than A Quarter of Earth’s Population
It might interest you to know that in the following 100-word paragraph, I’ll be making accurate assumptions about you as you read on. Tag along and see if I’m right.
As of today, the number of users on Facebook is greater than a quarter of the Earth’s population of humans. As you read this, I’m assuming you’re one of the 2.7 billion people on Facebook today. According to Forbes, every comment you make on the social media platform contributes to a pool of 510 thousand comments that are generated on Facebook every 60 seconds. What’s more interesting is, these figures are nothing when compared to the overall amount of data generated in the world on a daily basis. In other words, you could say that you now live in the Age of Data.
Living in the Age of Data, perhaps the thought of working with data on a professional level has crossed your mind. Either as an Analyst or Scientist, becoming a data professional promises so many perks and opportunities in this day and age. According to the Harvard Business Review, the field of Data has been praised as the “Sexiest Job of the 21st Century” and I couldn’t agree more. At the moment, you’re probably asking this very important question “What does it take to become a skilled data professional?”.
Although, the answer to this question has already been provided many times over in hundreds of articles and testimonies of different flavours scattered across the internet. Some say it only takes a single certification to kickstart your career in data, others maintain that it takes a combination of knowledge and hard work to break into the data sphere. Through my personal journey, as a Medical Research Professional and a Data Faculty, I’ve found that an intentional combination of these three key ingredients can help to kickstart one’s journey into data: a clear vision, knowledge with lots of practice and some relevant experience.
Having a clear vision of your prospects, particularly, in your industry of choice can help you focus on building your strengths as you amass the right knowledge with practice. Today, there are several platforms out there that offer one form of data-related certification or the other – making the best choice can get very overwhelming very quickly. The trick to making a good decision is to look for platforms you can relate to. For instance, a lot of the students I’ve interacted with, confess that after taking so many online courses from the big names like Coursera and Udacity, they always find their way back to a relatable and indigenous learning platform where they can enjoy a unique learning curriculum that reflects the realities of a local job market as well as a classroom full of familiar stories and faces. Finally, comes the most vital piece of the puzzle – a relevant experience. There is absolutely no substitute for knowing what it’s like to work with data in your field of interest. Therefore, it is important to pursue opportunities that provide such experiences. In your process of finding clarity, knowledge and experience, it is also important to remember that learning the necessary entry-level skills like SQL and Excel is perhaps the safest way to kick-start a data-driven career.
Why Excel and SQL
Many people have different reasons for wanting to associate themselves with the so-called “Sexiest Job of the 21st Century”. Some people simply want to improve their prospects at their current jobs, others are looking for a total career overhaul and some others are final-year students simply looking to invest in their self development in preparing for the graduate life. Whichever category you may belong, learning SQL and Excel is definitely a great way to start your journey, because having these skills on your resume will help get your foot through the doors of many employers.
To most people, the word “Excel” needs no introduction. It often refers to the Microsoft Excel spreadsheet package, the most common software of its kind, which provides users with the ability to mathematically compute data amongst other functions it performs such as Data Visualization. Excel is essentially a tool for efficient data exploration. Other similar spreadsheet packages also exist such as Google Spreadsheet, SPSS etc.
On the other hand, SQL is a query language used to interact with large shared data banks. Imagine all the data in the world is stored in several ‘data banks’, SQL provides its users with the ability to interact with these ‘data banks’ and collect every information they need in the most efficient way. SQL (otherwise known as SEQUEL) stands for Structured Query Language: it is a language developed nearly 50 years ago, yet is still one of the Top 3 data skills required by most employers in the job markets today. Much like KFC fried chickens, there are a secret blend of ingredients that has made SQL very unique from the 1970s till now and will continue to make SQL an irresistible skill to employers and employees – one of such ingredients is its ability to interact with relational databases that store millions of data in tables.
Why should you take this seriously?
Have you decided to learn Excel and SQL to become a Data Analyst, Scientist? Or do you wish to improve your valuable skill set at your current job? Perhaps you simply want to make a valuable investment in your self development as a student? Whichever path you’ve chosen to go, having a deeper understanding of the fundamental skills of Excel and SQL will always be an advantage for you. The role of a data analyst or a data scientist may be considered the “sexiest job” in the world today but such jobs are, quite practically, not meant for everyone. Some people are meant for much bigger management responsibilities, while others are meant for more conservative roles in their industry so long as they continue to do their best work with the most up-to-date and relevant skill sets. Ultimately, it is more important to understand that there’s nothing more sexy than an employee that possesses all the valuable skill requirements defined by the employer.