How to become a data analyst – complete career guide

In a field as constantly evolving as data science, one career track that’s relatively easy to understand is that of the data analyst. After all, a data analyst does exactly what the job describes: analyze data. Analyzing data is something we all do every day. Every one of us constantly learning and taking in new information (data), and then coming to many conclusions and making multiple decisions as a result (analysis).

So in the simplest terms a data analyst is required to do exactly that – gather information, organize it, and make informed (or findings-based) decisions as a result. Worded more as one might see on a job description; a data analyst is responsible for understanding the trends and insights that are revealed in massive data sets, translating that info into behaviors-based conclusions or projections, communicating these to stakeholders, and ultimately influencing if not determining an organization’s decisions and directions. Data analysts are often hired by companies to help inform or improve business practices. This guide walks through the necessary steps to become a data analyst, and contains detailed job description, salary information, and future job outlook.

What is a data analyst?

A data analyst takes data and uses it to help companies make better business decisions. A data analyst acquires information about specific topics and then interprets, analyzes, and presents findings in comprehensive reports. Many different types of businesses use data analysts to help collect and analyze data. As experts, data analysts are often called on to use their skills and tools to provide competitive analysts and identify trends within industries. 

A data analyst is similar to a data scientist but they’re not precisely the same job, but are often not responsible for creating the algorithms used for data discovery and acquisition. Rather than creating their own data projects, data analysts often find themselves tackling specific business tasks using existing tools, systems, and data sets. Both careers share a common goal: to discover how to use information to answer questions and solve problems for the benefit of their business/industry.

What does a data analyst do?

Data analysts translate numbers, trends, and trajectories into digestible and accessible information. Businesses collect data (i.e., sales figures, inventories, market research, profit margins, logistics, and transportation costs). A data analyst’s job is to take that data and use it to help companies make better business decisions. Often, the main goal of a data analyst is to solve issues that cost the company money and to help make decisions for expanding the business.

Some examples of a data analyst basic job functions include:

1. Estimating market shares
2. Establishing a price of new materials for the market
3. Reducing transportation costs
4. Timing of sales
5. Figuring out when to hire or reduce the workforce

Data analysts are responsible for collecting, manipulating, and analyzing data. Data analysts use systematic techniques, standard formulas and methods to analyze the relevant information. They then typically prepare reports detailing the results from their analysis.

Data analysts might perform basic statistics such as variations and averages for a particular product over a certain time period. They also predict yields and interpret the underlying frequency distribution of a set of continuous data. They use the standard methods of collection, analysis, and reporting when completing their tasks. Data analysts always protect the organization’s data, making sure that the data results produce consistent, reusable guidance.

The three steps to launching a data analyst career

Step 1: Earn a bachelor’s degree in information technology, computer science, or statistics

To best set yourself up for success in the field of data analysis, consider earning your bachelor’s degree in the field. A specific degree in data analysis is obviously best either information technology or computer science, while minoring in (or at least studying) applied statistics or data analysis. Also take computer science classes that emphasize project management and database management. Find an advisor or career counselor that is familiar with a data analyst career path.

Step 2: Gain data analyst experience

It is difficult to gain employment as a data analyst if you do not have any experience. Interning while in school is a good way to gain valuable experience and will help with insights about additional skill development and training. Even still, most people in technical careers start at entry level positions in this case including positions such as a statistical assistant or technician. These jobs will provide valuable on-the-job training and experience. Take as many in-house training classes as possible, especially ones focused on and incorporating analytical software programs and big data management. Experience, knowledge, and willingness to learn will help you rise to the level you desire and the qualifications sought after among hiring professionals.

Step 3: Advancing your career – consider a master’s degree or certificate program

An advanced degree will offer more job opportunities and ways to advance your career. Employers want candidates to have an array of knowledge and be familiar with the latest technologies and tools. Consider a master’s degree in data science, data analytics, or big data management. These programs will generally provide exposure to the newest software programs from experts in field. Many universities partner with corporations to create team assignments, internships, and capstone projects: which will gain invaluable real-world experience while earning an advanced degree.

Nervous about the cost or commitment required in pursuing a full master’s degree? Certificate programs are another viable option and a useful academic launchpad. These certifications are meant to give you a comprehensive overview of the subject in a comparatively short amount of time. There are outliers and variations, but essentially you can expect to earn a certificate in roughly 12 months. You don’t necessarily need a certificate in data analytics and visualization specifically, as you’re also able to pursue certifications in business analytics, predictive analytics, data visualization, and several other options.

To use one example, the University of Washington offers a Certificate in Data Visualization either online or at their Downtown Seattle campus. In about nine months, and over three courses you’ll learn Data Visualization Theory, Data Visualization Presentation, and Decision Making Through Data Visualization. You’ll reply on the most widely used tools to produce your visualizations (Microsoft Excel and Tableau) and additionally, you’ll become skilled at recognizing and visually implementing the design of data patterns based on “visual cognition and perception.”

Data analyst job description

• Figure out what questions are being asked and figure out if those questions can be answered by data.
• Determine technical issues with collecting and analyzing data, and design reports.
• Identify new sources of data and methods to improve data collection, analysis, and reporting.
• Collect, analyze, and report data to meet business needs.
• Distinguish trends and patterns.
• Report data in a comprehensive and repeatable way.

Skills needed to become a data analyst

Like business analysts, data analysts often possess sharp technical skills complimented by strong industry knowledge. They have a complete understanding of relationships that exist among the organization’s various databases and data sources. They obtain information using complex query statements and advanced database tools and techniques.

Analytical skills: Data analysts work with large amounts of data, including: facts, figures, and number analysis. They need to see through the data and analyze it to find conclusions.

Communication skills: Data analysts present their findings, and translate the data in understandable ways, be that in written documents, visual presentations, or verbally to a team of executives in a meeting. They need to write and speak clearly and be able to communicate complex ideas into easily understood terms.

Data visualization: A large component of effectively communicating the findings and insights that data analyst’s present is data visualization. As a data analyst, you’re going to have access to large quantities of data housed in data bases that it’s likely that many of the people you’re going to be talking to about your findings may have never even seen and wouldn’t understand if they did. Skilled data visualization can help that. By deciding on the right graphs to use, which charts work best for which audience, and how to scale the visualizations of your data, you’re setting the stage for how the story is being told. Choosing colors and graph designs may seem purely cosmetic, but there’s science involved in what our eyes are drawn to and how our minds process the images we see.

Creative and critical thinking: Data analysts must look at the numbers, trends, and data in order to formulate conclusions. Working with hard data obviously involves heavy critical thinking skills, but creativity and a curious mind can be just as important. By looking at the numbers through a creative lens, a good data analyst can generate compelling research insights that other companies or organizations might not have.

Attention to detail: Data is precise. Data analysts have to make sure they are attentive in their analysis to come to correct conclusions.

Math skills: Data analysts require highly developed math skills, particularly in statistics, to process numerical data.

Technical skills/tools: There are many technical skills and computer programs that a data analyst must have in order to be proficient. A few of these include: SQL, XML, JavaScript, R, Python, SAS, Hadoop, and other machine learning programs.

Microsoft Excel: One of the most important programs to have in your toolbox as a data analyst is actually one with which almost everyone in today’s workforce is familiar, Microsoft Office’s iconic spreadsheet software, Excel. Data analysts should have an expert handle on Excel and understand advanced modeling and analytics techniques available on the platform. This will mean quite a bit more than sorting and filtering, and focuses on slightly more complex functions like VLOOKUP. You might be amazed at just how much you can accomplish in data analysis with a relatively basic administrative platform.

Data analyst salary

The average salary for operations and research analysts (including data analysts) is $86,200 per year according to the Bureau of Labor Statistics (BLS) as of May 2020. There are many additional factors that affect the salary, including educational level, years of experience, certifications, and involvement in professional organizations. For the first five to ten years in this position, pay increases somewhat, but any additional experience does not have a big effect on pay. Most people move on to other jobs, such as data engineers, data architects, or data scientists once they have more than 10 years of experience in this career. The highest paying states for data analysts were listed as California, New York, New Jersey, Virginia, and the District of Columbia.

Data analyst job outlook

According to the BLS, employment of operations and research analysts (including data analysts) is projected to grow 25 percent from 2019 to 2029, which BLS rates as much faster than the average for all occupations. The metropolitan areas with the highest rate of employment for data analysts include New York City, Washington D.C., Chicago, Dallas-Fort Worth, and Los Angeles. Computer scientists are likely to enjoy excellent job prospects, because many companies report difficulties finding these highly skilled workers. Many companies are still trying to staff with the talent shortage in full force, and expect to see even more teams getting on board this year as they hurry to catch up to the rest of the market.