Data is a broad category that can be applied to careers within data science, business, finance, and marketing. Data is used to make business and financial decisions, inform marketing campaigns, and it’s the main material that data engineers work to create storage for. The amount of data produced each year has grown exponentially in the past 20 years. Big data has become a major driver of employment and our economy.
When people think of using data in a career they usually think of data science. Jobs like Data Engineer, who makes storage solutions; Data Scientist, who harnesses data to solve problems; Machine Learning Engineer, who automates data functions and teaches machines how to make decisions; and Data Analyst, who processes data to find useful insights.
But other careers also rely heavily on data in their day-to-day work. This primarily includes anyone with the term “analyst” in their job title. Business Analysts, Marketing Analysts, and Digital Analysts harness data to reveal powerful insights into trends, customer choices, customer satisfaction, and marketing information. Business Analysts rely mostly on Excel while Marketing and Digital Analysts use Google Analytics, Excel, and Tableau.
Financial Analysts and Investment Analysts utilize data to inform big decisions, but they work with financial data, stock market predictions, and financial modeling instead. Analysts in the finance sector use Excel every single day. Some also use Tableau, R, Python, and SQL, but these skills are usually only required for jobs that are located in financial hubs or tech venture capital firms.
Research Analysts are found in the highest concentration within the finance sector, but they can also work in marketing and any other industry that harnesses market research and data analysis to make their decisions. They also use Excel but might learn more advanced skills, depending on the industry they choose to specialize in.
Data is also an important aspect of an SQL Developer’s day to day. SQL Developers use the coding language SQL to create databases and applications. They also use other coding languages, developer tools, and Git.
Learning more about how data is used in each of these positions can inform which career path you’d like to embark on. Learning about data and how it’s used isn’t enough to land a job, though. You’ll need to learn more about data, data science, and data analytics to determine which skills and technologies you should learn.
