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Friday, December 2, 2022

Data Analyst Skills: Which are Most Important to Learn? – Dice Insights

What does it take to become a data analyst? What data analyst skills are necessary to climb to the top of the profession? As you might expect from a job requiring the analysis of huge datasets, data analysts must possess a broad portfolio of technical and soft skills, as well as a deep understanding of their core business.
Before we move into an analysis of data analyst skills, it’s worth taking a moment to define the job. Although some folks treat ‘data analyst’ as a synonym for ‘data scientist,’ the roles actually aren’t interchangeable. Data analysts use their skills and tools to provide their organizations with accurate analyses of (often massive) datasets. It’s different than data scientists, whose jobs are much more strategic and who often take a more holistic approach to the company’s data.
Lightcast (formerly Emsi Burning Glass) collects and analyzes millions of job postings from across the country. It’s a powerful tool for determining which skills employers want. It also breaks down skills into three categories: necessary, defining, and distinguishing skills. With that in mind, let’s break down what employers would like data analysts to know.
Lightcast defines necessary skills as “specialized skills required for that job and relevant across other similar jobs.” Necessary skills are the foundation; once mastered, a data analyst can focus on learning more specialized skills. Here are the necessary skills for data analysts:
All of these skills make sense, because data analysts must understand the fundamentals of their business (and business in general). They must evaluate a dataset’s quality and collection, manage its storage and flow, and then analyze it in the context of their organization’s overall strategy.
The next tier is what Lightcast calls “defining skills,” which are the day-to-day skills they need to fulfill a project’s tactical and strategic goals:
This is where the tools come in: data analysts must master the programming languages involved in databases (SQL) as well as analysis (Python). Knowledge of Tableau and the principles of data visualization are also key when it comes to showing the results of your analysis to key stakeholders.
After that come Lightcast’s “distinguishing skills,” defined as the advanced skills that product managers can use to differentiate themselves in a crowded marketplace:
For many data analyst roles, at least some of these skills are absolutely necessary. Mastering them can also allow an ambitious data analyst to jump into a data scientist role, which often requires knowledge of data architecture, data integration, and data validation.
Over the past 12 months, employers listed roughly 64,985 data analyst jobs, and the average time to fill a new position was 38 days, indicating a strong level of demand (for context, “hot” tech jobs such as software engineer can often take more than 40 days to fill). Data analyst is also considered a growth profession, with Lightcast estimating that open jobs will increase 11.8 percent over the next 10 years.
Lightcast lists the median data analyst salary at $70,461. Meanwhile, Glassdoor puts the estimated total compensation for a data analyst at $86,563 per year in the United States, with an estimated base pay of $76,262. Such salary numbers rise with experience; a senior data analyst could pull down an average of $93,000 annually, for example, and the number could go much higher depending on experience, skills, industry, and company.
The short answer is “no.” According to Lightcast, some 82.2 percent of open data analyst positions ask for a bachelor’s degree, while 3.2 percent of positions were fine with at least an associate’s degree. Only 3.9 percent of data analyst positions asked for a master’s degree. (Less than one percent of open data analyst jobs asked for a doctorate.)
“Soft skills” such as empathy and communication are critical in the vast majority of jobs, but they’re particularly important for data analysts, who must convey the results of their analysis to other stakeholders in an easy-to-understand way. Data analysts must also secure buy-in from team members and others who will eventually use the results of the analysis in their own work.
If you’re concerned about your soft skills, here are some quick tips you can use to improve them:
During any job interview, your interviewer will want you to describe how you used your data analyst skills to complete projects, overcome challenges, and deliver results for your previous employers. While you’re spinning your narrative, don’t forget to include how you’ve used teamwork and communication to achieve positive ends, as well. When it comes to data analyst jobs, it always pays to be well-rounded.
Curious to find out more about the state of the tech job industry? You’ve got the questions and we’ve got the answers. Tune in here.

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