Demand among employers for applicants with skills in data analysis has never been higher. Here’s how college students can capitalize on that demand — even if you aren’t pursuing a STEM degree.

Businesses across all sectors of the economy now have more valuable data on consumers than they know what to do with — literally. That’s why the number of roles requiring experience in data science and analysis has seen a tremendous 650% spike since 2012. Unfortunately for employers, supply of this coveted talent pool pales in comparison with demand, with only 35,000 people in the U.S. listing these requisite skills on their resume.

While these trends put enterprises in a difficult bind, they represent a fantastic opportunity for college students looking to secure a career in a field that is rapidly growing following graduation. This applies even if you didn’t plan your academic career around becoming a data scientist, analyst, or one of the dozens of other roles dedicated to processing and interpreting huge volumes of user data. Below we’ll explore five concrete steps that any college student can take to prepare for a career in data analytics, regardless of their major or focus.

  1. Learn SQL

For anyone wanting to dip their toes into data analytics, learning Structured Query Language (SQL) is an essential first step due to its special relevance to aspiring data engineers. It gives you the ability to query and manage data directly from within relational databases, a critical skill for data engineers whose job it is to process raw data and make it usable for their teammates. Learning the fundamental basics is crucial when it comes to understanding how the vast majority of data is leveraged and processed. Millions of rows of data can be altered in literally seconds with a well written procedure.

It also important to note that learning SQL also involves understanding how a relational database works conceptually. Learning both the conceptual aspects of the databases themselves and how to utilize SQL goes hand in hand and will speed up the process to become a master data manipulator.

Nevertheless, sometimes there are situations where SQL is limited in its capabilities as opposed to what must be done  — which brings us to our next item on the list.

  1. Learn a Programming Language

It is impossible to overstate the advantage that coding skills offer to those interested in the tech-heavy field of data analytics. Learning to code in languages like Python, Java, and R will not only enable you to develop websites, dashboards, and applications one line at a time, but equip you to clean, analyze, and visualize open data. It also empowers you to do higher level forms of data manipulation that SQL might not be suited for with the vast amount of libraries each of these languages have to offer.

While many colleges and universities offer classes in this discipline, there are also dozens of online resources available at a fraction of the cost, if not completely free. What’s most important is choosing a particular language, identifying specific coding skills relevant to your desired industry or position, and remaining patient and diligent. Coding takes time to master, but once you’ve grasped the fundamentals, more sophisticated capabilities become easier to learn. This applies to picking up other languages as well, as the main concepts and methodologies span across multiple languages.

Having multiple languages under your belt gives you a great boost in flexibility when it comes to choosing the best method to optimize your workflow and tasks. Tie that in with SQL and you’ve got the best of both worlds.

  1. Take a Statistics Class

With coding skills now on your resume, you may assume you’re ready to begin working with machine learning algorithms. But without a solid foundation in descriptive statistics and probability theory, you’ll find yourself ill equipped to glean the prescriptive and predictive insights offered by statistical modeling techniques and artificial intelligence tools.

There are multiple routes you can take to hone your expertise. If your course load is too heavy, take an intro Statistics course the next semester. If you don’t have the option of taking a college offered course, there are also plenty of online courses available on the subject to build your own Master’s degree equivalency in the subject — and if you do have that option, it could prove to be beneficial to do both. Supplementing coursework with additional online courses can accelerate the process of really solidifying that statistical foundation.

  1. Familiarize Yourself with Business Intelligence and Data Visualization Programs

Just as critical as your ability to interpret and process data is your ability to present it in a way that teammates and stakeholders will be able to understand. It’s important to familiarize yourself with programs like Tableau and Qualtrics; software designed to put raw data into a business context so that those without a background in analytics can leverage it when making key decisions. This will ensure that you’re not only capable of managing an organization’s data, but making it explicitly useful.

  1. Don’t Undervalue Your “Soft” Skills

For those already well on their way towards a STEM degree, keep in mind that a job in data analytics isn’t only about technical proficiency — it’s about communicating the value of data analytics to others. Data strategists must interface with executives and stakeholders throughout an organization, identify business problems, and translate those problems into the language of analytics. This requires strong communication skills, problem solving abilities, confidence, and a willingness to learn from others.

Most companies’ data analytics teams are large and collaborative, featuring a range of different professional skill sets and personal perspectives. When you’re coming together to solve a problem, you’ll not only need to advocate for the advantages and benefits of your own ideas, but also be prepared to listen to and evaluate the ideas of others. When you’re able to articulate your own ideas, the better you’ll be at ensuring your voice is heard at critical moments in the creative process.

An Investment In Your Future

The prospect of learning five complex new skill sets may seem daunting — and understandably so! The good news is that most of them can be mastered on your own time using online resources that are either free or relatively affordable. It is never too late to learn and doing so will only elicit positive opportunities for your future. There are literally thousands of them waiting for you — now’s the time to ensure you’re qualified for them.

 

Written by Heidi Wu

I have a background in software engineering with a BA in Computer Science. My relationship with Saatchi & Saatchi Wellness started in the Summer of 2017 when I came on as the Analytics and Data Science intern. I have officially been with the company since 2018 where I specialize in programmatic automation, data engineering, and dashboard visualizations. My goal is to optimize the analytics workflow and push for more innovative technologies within the healthcare marketing analytics realm. I am also a large advocate for the empowerment of women and underrepresented minorities in STEM. I take pride in guiding young individuals joining the field to a successful future. In my spare time, I rock climb and most importantly, play with my eskie, Kuro.

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