A data analyst is a problem solver who prepares and analyzes data to provide organizations with insights that help them make better business decisions. If you’re interested in a tech career involving both technical skills and interesting challenges, a career in data analytics may be a perfect fit for you.
So, what does a data analyst do, how much do they make, and how can you become one? In this guide, we’ll cover:
- Data Analyst Definition
- What Does a Data Analyst Do?
- Data Analyst Salary
- How to Become a Data Analyst
Data Analyst Definition
Data analysts collect, organize, and analyze data sets to help companies or individuals make sense of information and drive smarter decision-making. While all types of analysts conduct research to identify patterns and trends, data analysts leverage their technical skills — such as scripting, data blending, data visualization, and statistical programming languages — to help translate high-level business problems into well-informed potential strategies and solutions.
“A data analyst is someone with knowledge of Structured Query Language (SQL)/NoSQL, data presentation, and visualization languages who understands machine learning and data science, including statistics, math, linear algebra, and data structures,” says Chris Mattmann, chief technology and innovation officer at NASA Jet Propulsion Laboratory, and an adjunct research professor who teaches data science and big data at the University of Southern California. “A data analyst leverages these skills to apply to real-world structured and unstructured data sets to answer challenging business problems.”
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“When used correctly, data analysts can play a transformative role in an organization — they can drive decision-making; improve employee productivity, customer service, and company operations; elevate products; and better strategize to gain the competitive advantage within their respective industry,” says Theresa Kushner, who has more than 25 years of experience in data analytics and is head of the North American Innovation Center at NTT Data Services.
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Data Analysts vs. Other Types of Analysts
As the demand for data analysis increases, the industry is seeing more specialization in the field, according to Kushner.
What makes a data analyst different from other types of analysts in the technology industry? One key difference is that the general data analytics role is more comprehensive in its areas of analysis, while other types of analysts focus on a smaller subset of data analysis. Some different types of analysts include:
- Business intelligence analyst: analyzes products, markets, or trends to assess market strategies
- AI analyst: analyzes data by leveraging machine learning models
- Data quality analyst: analyzes the quality of data that organizations use for decision making
- IoT data analyst: analyzes data collected from Internet of Things (IoT) devices
“These specialty areas can be important depending on the company or industry the analyst works in,” explains Kushner. “However, they can also be niched and limited. When developing a career path, it is important to watch for opportunities that build on your experience, rather than limit it.”
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What Does a Data Analyst Do?
Data analysts can work in a wide range of industries, from finance and health care to government, manufacturing, and education — essentially any industry that uses data to organize its operations.
But regardless of industry, they help companies make strategic decisions by preparing and cleansing data, then presenting their findings. They work with both business and engineering teams and may coordinate their findings with different departments such as product management, data science, IT, sales, marketing, and finance.
According to Aswini Thota, a lead data scientist at Bose Corporation with over 12 years of experience in data analytics, a data analyst can help organizations make informed decisions by:
- Translating a high-level business problem into a measurable hypothesis
- Acquiring and blending required data assets to tell a complete story
- Generating compelling insights
- Offering data-backed scenario plans to quantify risk
Data Analyst Jobs and Tasks
A primary goal for data analytics professionals is to give companies information they can use to strategize more effectively and improve their business outcomes. They do this by acquiring and blending data assets to reveal a complete story behind the data.
In addition to generating compelling insights from data, analysts offer data-backed scenario plans to help companies determine the risk level of different decisions.
- Descriptive: uses data mining for business intelligence
- Diagnostic: mines data anomalies to understand why something happened
- Predictive: makes forecasts based on data
- Prescriptive: focuses on data optimization and simulation
- Cognitive: combines data with artificial intelligence (AI)
“As most if not all departments in an organization can improve their performance and services with data analytics, professionals in this role have the capacity to advance company performance overall,” notes Kushner.
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Data Analyst Salary
Being a data analyst can be lucrative — and the potential for high earnings increases with your experience in the field.
Entry-level data analyst jobs with 0-1 years of experience have average salaries of about $64,000 per year, according to Glassdoor. The average analyst in the U.S. earns over $70,000 per year. Senior-level data analysts with over 15 years of experience can command six-figure annual salaries of about $100,000. Those in the top range can earn as much as $157,000.
Mattmann offers an insider perspective on even higher salary potential in this field in certain industries. “You can make $120,000 to $140,000 a year for entry-level data analyst positions in government, and can make double that, with equity, in commercial roles,” he says. “Mid-career you can usually make around $180,000 to $200,000 in government roles, possibly double in commercial roles with equity.”
According to the U.S. Bureau of Labor Statistics (BLS), the job outlook for operations research analysts (a job category that includes data analysts) is much better than average. From 2021 to 2031, jobs in this field are expected to see 23% growth — considerably higher than the average of 5% for all occupations. “Data analysts are in high demand,” Mattmann says. “They are needed in all industries and all over!”
How to Become a Data Analyst
Studying computer science, business analytics, statistics, or any STEM subject in school can help you learn the core technical skills to become an analyst.
However, earning a college degree isn’t the only way to get started on a data analyst career path. It’s true that the majority of analysts — 65%, according to Zippia — hold a bachelor’s degree. Fifteen percent have a master’s degree, but the other 20% have taken a different route, learning skills elsewhere.
“While every data analyst requires the foundational knowledge of statistics, algebra, and calculus, you don’t need a Ph.D. in data science to become an analyst,” explains Kushner. “It helps instead to come with the technical skills that will not only get your foot in the door but will help you stand out from the crowd.”
Kushner emphasizes that this requires learning the skills needed for today, like data visualization, data management, and data cleaning, and the skills that will become high in demand in the near future, like:
- SQL, which is used to communicate with databases
- Python or R, which are statistical programming languages that help analysts perform advanced and efficient analyses
- Machine learning, which will accelerate the accuracy of data predictability
If you aren’t enrolled in formal education, how else can you break into the profession? You can target hands-on and experiential settings, such as virtual experience programs, bootcamps, certifications, and internships, to build your foundational knowledge.
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Even though employers are recognizing the value of data analysis in a virtual, global world, there’s also growing competition — especially since advanced technology is also being used to take over some facets of these jobs. To be competitive, Kushner advises those wishing to become data analysts to:
- Develop a portfolio of your work to demonstrate your competence and passion.
- Pay attention to the news to keep up with industry trends.
- Focus on leveraging industry predictions to position yourself uniquely for the role.
- Identify an employer that aligns with your passions and principles. This way, you’ll be more likely to enjoy your role and make meaningful contributions.
What Skills Does a Data Analyst Need?
A combination of soft skills and hard skills will serve you well in preparing to become a data analyst. “It’s important to build your technical skills, but also expand your soft skills, which will complement your technical skills to offer more advanced and unique insight,” Kushner says
Soft skills that are beneficial for this career include:
- Strategic thinking
- Critical thinking
- Business acumen
- Data storytelling
Hard skills you need for the field include:
- Scripting: SQL, Python, and R
- Data blending: Informatica, Alteryx, and SAS
- Data visualization: Excel, Tableau, Power BI, D3.js, and ElasticSearch
- Machine Learning: TensorFlow, Keras, PyTorch, and Pandas
- Practical database querying
- Data management
- Data cleaning
Want to know how a company’s data gets collected, stored, and ready for analysis? Learn about the data engineering career path.
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