The widespread use and collection of data is transforming our lives. Data sensors are everywhere—even in our smartphones. And organizations worldwide are cashing in to use this data to power their performance and optimize outcomes. They use data scientists, analytical structures, data sets, and more to utilize that data as they make decisions.
This transformation has grown the urgent need for data science and data analyst professionals with good data analysis skills. IBM predicts that the number of positions for data science and analytics talent in the U.S. will soon reach 2,720,000! That’s 364,000 new openings and includes 110,000 jobs specific to those with a data analysis career path. This could be data analyst jobs, data scientist, machine learning professionals, and more. The job descriptions will vary based on what your organization needs.
So what does a data analyst do? And why should you pursue a career in data analytics? The job outlook is exceptional for those with a data analytics degree. Read this guide to learn how to find the right data analytics job for you based on your skill set and education level. We’ve gathered the latest data analyst job description, as well as helpful tips for advancing your career in this booming industry.
Quite simply, you can expect great pay, interesting work, and excellent job security. Data analysts have lots of responsibilities in their daily work, involving solving problems, collecting data from a variety of sources, using analysis techniques to get information from raw data, writing reports, discussing findings with other managers and employees, and advising their decisions. This career is constantly changing, always different, and involves lots of attention to detail and focusing on quality. A career in data science or analytics also affords outstanding opportunity for advancement.
As a data analyst, you’ll serve as a gatekeeper for your organization's data so stakeholders can better understand it and use data to make strategic business decisions. You'll have data visualization and mining as part of your job description that will help you impact your organization. To start your career, you should first get a bachelor’s degree with an emphasis in data management or data analytics. It’s also helpful to earn related professional certifications such as:
Udacity Data Analyst Nanodegree
CompTIA IT Operations Specialist
CIW Data Analyst
Another good idea is to complete an internship while earning your credentials. This will make you an excellent candidate for numerous entry-level data analytics jobs, including:
Machine learning analyst
Business intelligence analyst
Computer science analyst
It’s important to note that even though job titles vary, the core component of any data analyst job description remains the same—interpreting data for better business decisions. That’s why data analysts are needed in almost every industry. Analyzing data trends is what keeps organizations competitive. So with a career in data analytics, you can choose to work in whatever industry you find most interesting. Some examples are:
Sales and marketing
Data analyst is definitely an upwardly mobile position. The difference between securing mid- and senior-level roles is on-the-job experience and additional education. But because there is such high demand for data analysts at any level, the projected job growth is positive for each tier over the next 10 years—ranging from 5% as a financial analyst to 25% as an operations research analyst. Data scientist, SQL operations analyst, database analyst, and other roles with unique job descriptions can open up when you pursue higher education.
Of course, the specific growth rate depends on what role and industry you enter (entertainment and tech pay the highest). And these factors, along with education, also influence your salary.
To move from an entry-level to a mid-level data analysis job, you’ll need your bachelor’s degree and two to four years of experience. To continue on to a senior-level data analyst job, you’ll need four to six years of experience, plus a master’s degree in data analytics.
Your annual salary, according to Zippa, will typically jump by $15,000 with every step up the ladder. So it’s definitely worth paying your dues in lower-tier positions and continuing your education. Machine learning, computer science, and SQL are great areas to study and learn.
Unlike other IT or data science jobs, data analysts work a fairly typical 40-hour workweek, Monday through Friday, with holidays off—which is why they have better job satisfaction. However, as with any business position, these hours and workdays can fluctuate due to organization or industry demands. Their job description may include being on-call if needed.
So what does a data analyst do every day during their work hours? Daily work and activities focus on using data to make sound, business-critical decisions. Basically, they help organizations answer key questions like how to improve, what to do next, or how to shift gears.
If you’re employed by a smaller company, you may analyze multiple data projects simultaneously, often working on your own. Whereas, if you work for a larger organization, you may work within a team and focus on one large project or data sets at a time.
Common activities include:
Collecting data and streamlining the collection process through automation.
Spotting patterns in data (e.g., the trends and insights).
Producing internal and client-facing reports to help management see these trends and capitalize on areas for improvement.
Collaborating with others—from sales and marketing to data architects and database developers to department leaders and executives.
As you progress on your data analytics career path, you’ll get more responsibility and solve more challenging problems. Here’s a brief outline of how your typical day-to-day activities may evolve:
Entry-level. You’ll analyze results (the data) from various projects and business systems and work with clients or project leaders to design efficient solutions for improving them. Your jobs can range from data dredging to pattern mining to statistical analysis, and you’ll work under a supervisor.
Mid-level. You’ll still be using statistical analysis, data mining, and other data analysis skills to develop successful business solutions. But now you can use your experience to lead peer-based teams (in larger organizations) and be more creative in the procedures, methods, and approaches that you employ. You’ll still report to a supervisor or manager.
Senior-level. You’ll continue to perform all of the same tasks as before (analyze data, form business solutions, work with business leaders, etc.), but you’ll now train and manage junior analysts. You’ll also be able to make more independent decisions thanks to your seasoned knowledge and experience, and you’ll report to your department’s leader—typically in a director, VP, or C-level role.
If telling stories from data and information sounds exciting (and it is!), then a career in data analytics may be a perfect fit. It offers the ideal balance between working independently and contributing within a larger group.
Those who are successful in this occupation are analytical and strategic thinkers with cross-functional communication skills. They’re also highly focused and determined and excel in:
Asking the right questions.
Gathering and sorting critical information.
Using business acumen to deliver key insights.
It’s the ongoing satisfaction of uncovering and solving problems that makes this profession so rewarding, which is why most data analyst professionals enjoy their jobs. With the ability to work in an industry that you’re passionate about, earn an excellent wage, and write your own ticket for career progression, what’s not to love?