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Technology is advancing every day – and each new hardware product, software package and even cell phone game creates new data sources. The World Economic Forum estimates that in 2023, industrial businesses alone will create 130 zettabytes of data, information that can transform companies that use it to optimize their decision-making. Unsurprisingly, demand is rising rapidly for professionals who can help organizations optimize and utilize their data. Lightcast Analytics predicts job openings for data analysts will increase by 18.4% by 2032. So what does a data analyst do, and what does a career in this booming field look like?
Data analysts work with large data sets to ensure that the information they contain is high-quality or “clean” and use tools like software and programming languages to identify patterns or trends in that data. They share those findings by creating visualizations, presentations or written reports. Depending on their specific role and their company’s needs, some data analysts may also be involved in collecting the data.
Individuals’ pathways into data analysis roles vary significantly. A bachelor's degree in a quantitative field such as mathematics, statistics, computer science or engineering is required for many positions in this field. Some employers require a master’s degree, especially for more advanced positions, like data scientist roles. However, it is also possible to enter the field without a related degree by demonstrating that you have certain technical skills, such as by earning industry certifications.
According to Dr. Nimet Alpay, chair for Franklin University’s M.S. in Data Analytics program, professionals who hope to become data analysts or who wish to advance their careers should focus on developing skills in the following areas.
Programming
Data analysts and scientists must be able to write code, analyze data, develop or improve algorithms and use data visualization tools. Proficiency in programming languages like Python, R and SQL and data visualization tools like Tableau and Power BI is critical in these roles.
Math
Data scientists use statistical methods to collect and organize data. A good understanding of statistical modeling, machine learning algorithms and predictive analytics is essential for advanced roles in data analytics.
Logical thinking and problem-solving
Data analysts must understand statistical models and how to use them to analyze data. In advanced functions, they also need to be able to design and develop models. They also need to be effective problem solvers who can find solutions to challenges they encounter in their work, whether that is data collection and cleaning or developing statistical models and algorithms.
Communication
Data analysts must communicate their findings effectively to technical and non-technical audiences. Often, this means translating complex technical information into accessible insights that can be used to drive business decisions.
Collaboration
As data analytics projects often involve working with cross-functional teams, having strong teamwork and collaboration skills is crucial to success.
Before you can advance in your career as a data analyst, you’ll need to develop core skills and a portfolio of work you can share with potential employers. Often, the best way to develop those skills is through an entry-level position.
Entry-level data analyst roles involve collecting, cleaning and analyzing data to extract insights and make data-driven recommendations. Data analysts typically work with structured data and use basic analytical tools and techniques. From March 2022–March 2023, the median advertised salary for data analyst positions requiring 0 years of experience was $59,600, according to Lightcast Analytics, a leading labor market research firm.
But what comes next after your first job in data analysis, and how much do data analysts make further along in their careers? Data analyst career progression depends on where your interests lie within the field as well as your preferred industry and workplace setting. In several years, you may even find yourself in a role that does not yet exist today since data analytics is rapidly evolving as technology advances. For example, future roles will likely focus more on tools like machine learning and artificial intelligence.
Even with those changes on the horizon, exploring potential career paths can help guide your decisions around education, certifications and employment. Simply gaining experience and taking on additional responsibilities can result in significant pay boosts. You can also choose to advance your career by specializing in a specific field, entering management, or continuing your studies to become a data scientist.
If you’ve entered the field as an entry-level data analyst, you may wish to continue on that trajectory by moving into positions of increasing responsibility and oversight. First, you might move into a senior data analyst role, where you will take on more complex projects and work with larger datasets. Senior data analysts may supervise junior analysts and collaborate with stakeholders across different departments to identify and solve business problems. You might then move into supervisory positions. Specific titles can vary between organizations but may include:
Data Analyst Manager
Data analyst managers are responsible for overseeing a team of analysts and scientists, managing projects and budgets and driving strategic decision-making using data-driven insights.
Director of Data Analytics
The highest-level data role in an organization, the director of data analytics (or chief analytics officer at some organizations) is responsible for driving the organization's data strategy, overseeing analytics teams and working closely with executives to ensure that data is used to drive business growth and competitive advantage.
Another path forward in data analytics is to specialize in a specific area of data analysis. Throughout the data analysis industry, educational requirements tend to vary by employer, though there are general hiring trends to consider for each role. Examples of specialist data analyst roles include the following.
Business Intelligence Analyst
Business intelligence analysts use data about their company’s customers, revenue and competitors to identify opportunities for growth and improvement. Typically, business intelligence analysts hold a bachelor’s degree in a field such as computer science, data analysis, or statistics. They may also hold additional certifications.
Market Research Analyst
Market research analysts collect and analyze data on consumer preferences and behavior, often using focus groups and surveys. Most marketing research analyst positions require a bachelor’s degree in a field like marketing or business, and many professionals in this role hold specialist certifications.
Finance Analyst
Financial analysts use data to guide investment decisions for individuals and institutions like banks. These positions often require a bachelor’s degree in a subject like finance or mathematics. Advanced qualifications for these financial analysts may include advanced business degrees or Chartered Financial Analyst (CFA) certification.
Healthcare Analyst
Healthcare analysts use data from healthcare facilities or insurance companies to identify trends and make recommendations to improve patient outcomes and reduce costs. Many healthcare analyst positions require a bachelor’s degree, typically in a field related to math, science, or IT.
Operations Research Analyst
Operations research analysts use business data to improve how businesses function, often by streamlining complex processes like supply chain management. Most operations management analyst positions require a bachelor’s degree in math or a related field. Many also require an advanced degree in fields such as operations research or applied mathematics.
Management Analyst
Management analysts help organizations address challenges ranging from team structure to product-market fit. Often, these roles involve collecting data through surveys and conversations with stakeholders. Most management analysts have a bachelor’s degree in a business-related field, and many employers prefer candidates with a master’s degree in business analytics.
If you want to dive deeper into not only analyzing data but also building the tools used to do the analysis, you may wish to pursue additional education and become a data scientist. Usually, data scientist roles require an advanced degree such as a master’s or doctorate and high-level knowledge of applied mathematics and statistics.
The median advertised salary for a data scientist is $124,700, and senior data scientist positions and management roles can come with significantly higher pay.
Entering or advancing in data analytics can seem daunting, especially if you don’t have a technical background. However, programs like Franklin’s Graduate Certificate in Data Analysis can prepare you for in-demand positions regardless of your current industry or role.
This online program, which does not require a STEM degree or placement tests, boosts your knowledge of statistics, databases, data visualization, data mining and big data technologies using high-demand tools such as R and Tableau. In just eight months, you’ll gain job-ready skills while working on real-world projects.
The graduate certificate also earns half of the required credit for three different master’s degree programs at Franklin: the M.S. in Data Analytics, M.S. in Business Analytics and M.S. in Health Informatics. These degrees offer excellent preparation for specialized data analytics positions and management roles.
Learn more about how Franklin can help you move your career forward.