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How to Become a Data Analyst: A Beginner’s Guide

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It’s no secret we’re living in a data-filled world. The widespread adoption of personal computers, mobile devices and the internet across the globe has paved the way for the production, collection and transmission of data at a scale that would be beyond comprehension just decades ago.

But that data is only helpful if you know what to do with it. That’s why companies are hiring data analysts and other tech professionals to compile, refine and translate that data into meaningful insights to improve their business efforts.

If this career path interests you, you likely have a few questions about what to expect on the road ahead. We’re here to provide you an in-depth look at what data analysts do, the skills and training they need, and other information would-be analysts should know before pursuing this career.

So keep reading to find out how to become a data analyst and determine if this is the right path for you.

What does a data analyst do?

The job title itself tells you enough to know that these professionals spend their days analyzing data. But there’s more to it than skimming spreadsheets and offering suggestions. These professionals often work on highly-specialized projects. They may be responsible for examining the effectiveness of digital advertising spending, projecting market demand or evaluating the value of a new protocol for employees. Effectively completing these tasks requires a deep knowledge of the data inputs they’re working with.

While the details will depend heavily on the type of project or question an analyst is attempting to answer, most data analysis follows a similar routine. First, analysts need to get a handle on the current data landscape for a given project. Then they determine what data is most useful or relevant to gather and identify potential information gaps to consider.

Next, analysts must organize and “clean” the data they’ve gathered—this includes removing duplicative data and providing standardized formatting. This prepared data is then used as an input for calculations and analysis that is tailored to fit the question or project. The final output of their work can take many forms, but often analysts are tasked with developing data visualizations that help illustrate their findings and recommendations.

Sound like a lot? It certainly can be, and in some organizations this data analysis work is broken down into further specialized roles.

What are some common data analyst job titles?

While it’s true many employers will use “data analyst” as the primary job title for this type of work, there are other common variations out there. Other potential titles include:1

  • Business analyst
  • Database analyst
  • Business consultant
  • Data quality analyst
  • Analytics consultant
  • Data specialist

What skills and qualities do data analysts need?

Working with data draws on a mix of valuable hard and soft skills. Our review of data analyst job postings found the following technical skills were most commonly sought after:1

  • SQL
  • Tableau®
  • Python®
  • Microsoft Excel®
  • Data management
  • Data warehousing
  • SAS®
  • Data mining
  • Data visualization
  • Business process analysis
  • Economics

As you can see, many of these skills focus on a candidate’s competence with the systems, platforms and tools commonly used. But tools are only as effective as the people using them. So what soft skills do successful data analysts possess? Our job posting analysis found the following:1

  • Communication skills: Data analysts need to be able to share their findings with stakeholders in easy-to-understand terms and be prepared to answer or address follow-up questions.
  • Collaboration: This obviously comes into play if you’re working as part of a team of analysts, but you may also need to work closely with the people who use the systems generating data in order to properly understand what you’re working with.
  • Problem-solving: This skill comes in handy in a variety of ways, but often there’s a disconnect between what an organization would like to know and what data they actually have available. Analysts will sometimes need to get creative when determining how to bridge that gap.
  • Research: Data analysts need to be comfortable digging for answers. That can come in the form learning the finer points about what a piece of information actually represents, learning how others have approached answering similar questions or exploring the root cause of outlier data.
  • Attention to detail: Analysts need to verify they’re using the right information and metrics for the task at hand and be keenly aware of how small mistakes can cause large issues.
  • Planning and organization: Using data to answer questions is often an exercise in pulling information from different sources. These systems can become incredibly complex, so the ability to logically map out where data is being pulled from and where it is flowing is a big help.

How do you become a data analyst?

Unlike becoming a doctor, the steps to becoming a data analyst are not really set in stone; there are several paths to pursuing this profession. One thing you can be fairly certain of, though, is the need for a formal education.

Our analysis of data analyst job postings found that 82 percent of employers were seeking candidates with at least a Bachelor’s degree.1 Subjects like computer science, statistics, economics and applied mathematics can all provide a solid foundation for analysts, and modern Data Analytics Bachelor’s degree programs aim to provide a concentrated focus on the skills needed for technical data analysis roles.

Beyond the classroom, there are other opportunities for building data analysis skills. Some aspiring analysts get started in this field by first working in positions with job duties that overlap with a data analyst skillset. For example, digital marketing specialists working with Google Analytics to better understand website performance or finance professionals whose work involves complex Excel spreadsheets and reporting.

Roles like these can provide an excellent foundation of skills to build upon. Additionally, for those with at least a little data know-how, there are several sites offering free data sets to use for practice projects or competitions. These online opportunities can provide a great way to refine your skills and potentially build a portfolio of work.

Are you destined to become a data analyst?

If you’re interested in a data analyst career, there’s a lot to take in here. But hopefully with this overview you’re now familiar with how to become a data analyst and the work they’re responsible for.

Sound like something you’re interested in? Learn more about how we can help prepare you for success by exploring our Data Analytics program page. (analysis of 88,346 data / data mining analyst job postings, June 1, 2019 – May 31, 2020)

Python is a registered trademark of The Python Software Foundation.
Microsoft Excel is a registered trademark of Microsoft Corporation.
Tableau is a registered trademark of Tableau Software.
SAS is a registered trademark of SAS Institute, Inc.

Will Erstad

Will is a Sr. Content Specialist at Collegis Education. He researches and writes student-focused articles on a variety of topics for Rasmussen College. He is passionate about learning and enjoys writing engaging content to help current and future students on their path to a rewarding education.


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