Skills and tips to maximize it

As data becomes crucial to all functions of organizations, the need for accurate analysis also increases alongside it. This is why data analysts are more valuable than ever, but how does that translate into the actual salary of data analysts? And if you’re applying for this role, what can you focus on to maximize your earning potential?

Before moving forward, let’s take a moment to distinguish between data analysts and data scientists. Data analysts typically focus on smaller, more tactical data issues. Data scientists, on the other hand, take a more holistic approach to business data and often provide more strategic analysis. The terms are not interchangeable.

What is clear, however, is that data analysts and data scientists are in high demand. A Harvey Nash report, the result of a collaboration with the Massachusetts Institute of Technology CISR and CIONET and released in late 2021, said the acute shortage of data analytics skills can dramatically increase your hiring potential.

The World Economic Forum’s Jobs of Tomorrow report, released in 2020, ranked data scientists as one of seven high-growth emerging occupations, with data analysts coming in fifth place. It is clearly a profession with many advantages.

What is the average salary of a data analyst?

According to Burning Glass, which collects and analyzes millions of job postings across the country, the median salary for a data analyst is $73,067, but that can rise significantly with the right combination of experience and skills. skills.

Burning Glass also estimates that data analyst jobs will grow 12.3% over the next 10 years. Currently, there have been 100,393 data analyst job openings in the past 12 months, and the average vacancy takes 39 days to fill, indicating a healthy level of demand.

According to Glassdoor, the total estimated salary for a data analyst is $86,563 per year in the United States, with an estimated base salary of $76,262 per year. A senior data analyst can expect to earn $93,000 per year.

What are the most valuable skills for a data analyst?

Analyzing these job postings, it’s clear that the data analytics hard skills most in demand by employers include:

  • Data analysis
  • SQL
  • Python
  • Picture
  • Microsoft Power BI
  • Data science
  • Data quality

Additionally, employers often want data analysts to have “soft skills” such as communication, problem solving, research, writing, and teamwork/collaboration. Depending on the specialization they pursue, data analysts may need to master analytical tools and software specific to healthcare, manufacturing, and other industries.

Shounak Simlai, vice president of data strategy and business intelligence at ActiveCampaign, thinks that among the best skill sets for data analysts, data modeling skills in Excel and SQL are the bare bones. minimum. “In addition to that, I would recommend that data analysts be familiar with statistical modeling programs like R,” he said. “It’s also important to have coding experience and an understanding of data infrastructure, in order to interface with data engineering.”

He said a successful data analyst must be able to collect data, then find patterns in that data and generate reports to make sense of it all, telling simple, digestible data stories that provide key stakeholders with clear and actionable information.

What skills do you need as a data analyst?

At the most fundamental level, data analysts need to master data visualization (such as Tableau) and analytics/BI (via tools such as Looker) skills. In other words, you absolutely must be able to process the data in a form understandable by all stakeholders.

“Even though everyone has probably heard that data is the ‘new oil’, not all of us understand the true meaning of this slogan,” said Jakub Kubrynski, CEO and co-founder of DevSkiller. “Of course, it is obvious that oil is a precious resource and that it has to be extracted and processed in one way or another. But to get the most out of it, you also need to be able to refine it and deliver the final product to gas stations. The same goes for data.

Kubrynski said it’s not enough to extract numbers and information from the organization’s systems and organize them into simple reports and dashboards: “You need to be able to translate your insights into actionable recommendations. and communicate them to stakeholders… Therefore, the single most important soft skill you should focus on as a data professional is the ability to communicate clearly and concisely. also be great storytellers.”

Adding the ability to manage ambiguity and communicate nuance to these stakeholders is also essential. Data analysts regularly communicate results through oral presentations, PowerPoint presentations, etc.

What programming languages ​​do data analysts learn?

Kubrynski said data analysts, like other data professionals, should know various programming languages ​​and frameworks, especially Python, Perl, R, Scala and of course SQL. “But acquiring or developing coding skills in one or more of these languages ​​is just the beginning,” he said. “What really matters when it comes to staying competitive in the job market is the ability to apply those skills to solving practical business problems.”

Do I need certifications to become a data analyst?

As with many IT skills, there are many certifications on the market that you can consider to increase your value as a data professional.

In addition to Stanford’s famous machine learning certification offered by Coursera, the top three that Kubrynski would recommend are:

“Nevertheless, each certification, even the most prestigious, can only serve as an indication of theoretical knowledge,” he added. “In most, if not all, recruitment processes for tech-related roles, adding a certification to your resume can only help you sift through the resume screening process.” (Regardless of your certifications, you’ll need to prove your practical skills during the job interview process.)

Simlai highlighted a wide range of certifications data analysts should consider to improve their value proposition, including:

He also thinks it’s worth studying the CareerFoundry data analytics program and the Springboard Data Analytics career path.

How can I negotiate a better data analyst salary?

Kubrynski thinks the salary negotiation tips and tricks for analysts and other data professionals are generally the same as for other positions. ” Familiarize yourself with salary benchmarks for your industry and geographic location, focus on the practical dimension of your knowledge and show the real value you can bring to the organization, from problem solving to saving money money and increased income,” he said.

Above all, do not be afraid to refuse an offer that does not satisfy you. “Market demand for data science skills is growing rapidly,” Kubrynski said. “You can certainly afford to be selective.”

For Simlai, the best salary negotiation tactic he can think of is three words: research, research, research! “Understand what the market is currently paying for comparable roles,” he said. “The negotiation must be win-win for both parties. Focus on framing your pitch about what you can help them achieve within six months of getting started.

Sean N. Ayres