What are the most important to learn?
What does it take to become a data analyst? What data analyst skills are needed to rise to the top of the profession? As you would expect from a job that requires the analysis of huge datasets, data analysts should have a wide range of technical and soft skills, as well as a deep understanding of their core business.
Before moving on to analyzing data analyst skills, it’s worth taking a moment to define the job. Although some people treat “data analyst” as a synonym for “data scientist”, the roles are actually not interchangeable. Data analysts use their skills and tools to provide their organizations with accurate analyzes of (often large) datasets. This is different from data scientists, whose jobs are much more strategic and who often take a more holistic approach to business data.
Which data analyst skills are most important?
Lightcast (formerly Emsi Burning Glass) collects and analyzes millions of job postings across the country. It is a powerful tool for determining the skills employers are looking for. 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 this job and relevant to other similar jobs”. The necessary skills are the base; once mastered, a data analyst can focus on learning more specialized skills. Here are the skills needed for data analysts:
- Data management
- Project management
- Data quality
- business process
- Data gathering
- Customer service
- Business analysis
- Key Performance Indicators (KPIs)
All of these skills make sense, because data analysts need to understand the fundamentals of their business (and the business in general). They need to assess the quality and collection of a data set, manage its storage and flow, and then analyze it in the context of their organization’s overall strategy.
The next level is what Lightcast calls “definition skills,” which are the day-to-day skills they need to achieve the tactical and strategic goals of a project:
- Data analysis
- Microsoft Power BI
- Data science
- Data visualization
- business intelligence
- Data warehousing
- Extraction Transformation and Loading (ETL)
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 data visualization principles is also essential when it comes to showing the results of your analysis to key stakeholders.
Next are Lightcast’s “distinctive skills”, defined as the advanced skills that product managers can use to differentiate themselves in a crowded marketplace:
- Data validation
- Apache Hadoop
- Data architecture
- Data integration
- Data structures
- SQL Server Reporting Services (SSRS)
- Visual Basic for Applications (VBA)
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.
Is data analysis a popular profession?
Over the past 12 months, employers have listed approximately 64,985 data analyst jobs, and the average time to fill a new position was 38 days, indicating a high level of demand (for context, jobs “hot” technologies such as the software engineer can often take longer than 40 days to complete). Data analyst is also considered a growth profession, with Lightcast estimating that open jobs will increase by 11.8% over the next 10 years.
How Much Do Data Analysts Earn?
Lightcast lists the median salary for data analysts 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 salary of $76,262. These salary figures increase with experience; a senior data analyst could make an average of $93,000 per year, for example, and the number could increase significantly more depending on experience, skills, industry, and company.
Do Data Analysts Need Advanced Degrees?
The short answer is no.” According to Lightcast, some 82.2% of open data analyst positions require a bachelor’s degree, while 3.2% of positions were acceptable with at least an associate’s degree. Only 3.9 % of data analyst jobs required a master’s degree (Less than one percent of open data analyst jobs required a PhD.)
Do data analysts need “soft skills”?
“Soft skills” such as empathy and communication are essential in the vast majority of jobs, but they are particularly important for data analysts, who must communicate the results of their analysis to other stakeholders in a way easy to understand. Data analysts also need to get 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:
- Listen to your colleagues and team members. Their concerns are valid.
- If your company offers soft skills assessment and training (and many do), you should make an effort to enroll there.
- Keep your comments polite and constructive, regardless of the circumstances.
- Don’t just give feedback. Encourage your colleagues and manager to share your progress as often as possible.
- Rely on your mentor and any informal advisers to help you with your interpersonal skills.
- If you have the ability to set your performance goals and evaluation, request that your soft skills be evaluated regularly. Your manager will approve of your proactiveness (and your company may already have such criteria in place).
In any job interview, your interviewer will ask you to describe how you used your data analyst skills to complete projects, overcome challenges, and deliver results to past employers. As you spin your story, don’t forget to also include how you used teamwork and communication to achieve positive goals. When it comes to data analyst jobs, it always pays to be well-rounded.