In 2012, IBM revealed that 2.5 quintillion bytes of data were being created per day — an enormous sum that humankind had never known before. Since then, the volume of the world’s data has not only continued to increase, but it’s arriving at a faster and faster pace.
However, data by itself doesn’t have much value. After all, a pile of numbers and data files is just that: a pile of numbers and data files. The real value of data comes from making sense of the abundance of information. That’s why businesses and organizations across countless industries are investing in forward-thinking data talent — to leverage its predictive power, craft smart business strategies, and drive informed decision-making.
The sharp and strategic people who do this job are data scientists, data analysts, machine learning engineers, and business intelligence analysts — among other titles — and these professionals are in high demand. In 2018, the jobs platform Glassdoor ranked data scientist as the Best Job in America for the third year in a row, with a median salary of $110,000 and more than 4,500 available positions. Additionally, five other data- and analytics-related roles made the list of the top 50 jobs, ranked by number of openings in the field, salary, and overall job satisfaction.
Companies are quickly recognizing the vital need for data knowledge, impacting a vast array of industries including eCommerce, health care, finance, and sales — to name a few. In order to stay competitive and grow their businesses, leaders are investing in their future by strategically training and hiring talent to ensure proficiency in key skills.
Three of the most prevalent technologies transforming how we understand and use data are SQL, Python, and machine learning — and all are great entry points into the field. The first two are programming languages used to gather, organize, and make sense of data. The last is a specific field in which data scientists and machine learning engineers, using Python and other technologies, enable computers to learn how to make predictions without needing to program every potential scenario.
What You Can Do With Essential Data Skills
You can get started with SQL, Python, and machine learning, three of the most useful data tools, without any formal background. However, each topic has a different set of fundamentals that you’ll need to understand as you progress in your learning. For example, Python will expose you to the world of object-oriented programming, while SQL will expose you to database design concepts. Machine learning will require a good understanding of data analysis.
Dipping your toes in this uncharted water may seem daunting — but it shouldn’t! There’s so much opportunity in the data field for growth, whether or not you’re seeking a full-time role. No matter your position or industry, this knowledge can take your hireability to the next level. Here are just some of the things you can do with data expertise:
- Become a skilled problem-solver. Programming languages like SQL and Python teach you problem-solving skills that are applicable in many business scenarios you’ll encounter.
- Be more cross-functional. Having key programming and data skills under your belt makes it easier to work with teams across your organization. Being able to speak the same language as software engineers, business intelligence analysts, and data professionals helps streamline requests, bring clarity to the workflow, and provide insight into technical action items.
- Build the technology of the future. Data skills enable you to help build new, groundbreaking technologies, including web applications, machine learning models, chatbots, and much more.
- Expand your career potential. Based on previous projections from the management consultancy firm McKinsey & Company, IBM predicts that by 2020, the number of data science and analytics job listings will grow by nearly 364,000 to about 2.72 million.
- Improve communication. Data professionals must communicate to non-technical audiences — including stakeholders across the company — in a compelling way to highlight business impact and opportunity. At the end of the day, those stakeholders have to act on and possibly make far-reaching decisions based on data findings.
Want to learn more? In our paper A Beginner’s Guide to SQL, Python, and Machine Learning, we break down these three essential technologies. The skills go beyond data to bring delight, efficiency, and innovation to countless industries. They empower people to drive businesses forward with a speed and precision previously unknown, and now’s a great time to dive in.
Download the paper to learn more.
Boost your business and career acumen with data.
Find out why machine learning, Python, and SQL are the top technologies to know.