The words “data analyst” produce a mental image of someone working behind a computer in a dark room with many complex charts. That, or someone working in a millennial startup with a cup of coffee and a Mac computer. In my experience, few understand all the benefits of working as a data analyst.
So, why be a data analyst? Data analysts enjoy high growth potential in the current data boom, diverse workloads with technical and interpersonal tasks, flexible hours, remote working, respect at work, young teammates, fun working cultures, creative freedom, intelligent coworkers, interdepartmental cooperation, access rights to exclusive data, cutting edge systems & software, and comfortable $60k – $80k salaries in the United States1.
Let’s look at these more closely.
Great Growth Potential in the Data Boom
You probably already know it, but we’re living in a data boom. It’s common amongst those working in big data to say the world as we know it is only using 5% of available data. We’re collecting so much, so fast, it’s difficult for companies to even maintain a trailing position. They’re falling way behind.
While it’s not great for companies, it’s great for the data analysts that they hire. There is a huge demand for data-savvy profiles, even outside traditional data departments such as Business Intelligence.
This dynamic means data analysts are in a favorable position. Even if they don’t want to work in a “traditional” data analyst department, data analysts can work in all of the following departments:
- digital marketing,
- sales,
- logistics,
- retail,
- finance,
- manufacturing,
- waste,
- delivery,
- order fulfillment,
- customer satisfaction, and more broadly,
- non-profit humanitarian companies.
While data scientists and business intelligence analysts dig deep, data analysts are at the forefront of any data activity. Being at the forefront means they have the essential data skills, and can develop them further to move either up the corporate ladder into management positions OR into more statistics-oriented positions like data science and BI.
In other words, in today’s data boom, data analysts have seemingly endless possibilities for growth.
Diverse Workloads with Technical and Personable Tasks
If growth potential is a high-level advantage, a diverse workload is a day-to-day advantage. Data analysts don’t repeat one consistent task day in and day out. Instead, they are called upon to solve a host of problems and investigate data in all departments of the company.
More importantly, they spend about an equal amount of time working on technical analysis as on using the results of that analysis to solve business problems with operational teams. For many analysts, this gives them the best of both worlds. They get the intellectually stimulating side of data analysis and the pleasure of working with people.
Flexible Working Hours
Unlike teams that need to work within the normal 9 – 5 working day in order to communicate externally or cooperate on large cross-company projects, a data analyst’s work itself is highly independent. S/he may need to check inputs and outputs with other teams, but the analysis itself — the bulk of her time — is an independent activity.
This means s/he has some flexibility in her working hours. For example, if a data analyst works with a sales representative to determine the most valuable recurring customers over a 20 year period in the company, she needs to sit down with the sales representative to understand project requirements. However, the data analyst can perform the entire analysis herself.
In this case, she can choose the hours she wants to perform said analysis. Since there is no impact on the quality of her work, many companies allow this on an informal basis. As long as s/he works her hours, there is no reason for the company to object.
Remote Working Possibilities
In addition to having flexible hours, data analysts can easily work remotely on their analysis, especially when the task is a big one that takes up several days’ time. In fact, many analysts claim that working remotely helps them stay focused.
At work, there’s always the possibility that colleagues come to ask questions (work-related or not), so you’re never completely alone to focus on complex analyses. However, when you’re working remotely, you can dig deep on complex questions. In many cases, you produce better results, faster.
Young Teammates
We’re living in a data boom, and it began not more than 30 years ago. And in those 30 years, data technology has developed at a rapid pace. This means that there are few “aged” professionals who lived the boom and technological development in years when they were able to adopt them. Data analysts, in other words, are typically a younger crowd.
When I first got started working with data, the most senior business intelligence manager in the company was 31. Everyone under her was younger than 30, and highly competent. Perhaps the most potent benefit of having young teammates is actively not having “outdated” managers who can’t perform the tasks themselves. This can be a killer in many organizations. When outdated managers want to micromanage their teams, it creates confusion and frustration.
Young teammates prove to be a better dynamic for maintaining cohesion. Not only that, but they’re typically very fun.
Fun Working Cultures
The youthful nature of data analysis also makes for a fun working environment. It’s not just because young people are “fun,” but it’s also a top-down effect. Companies need to create cultures and benefits that speak to the younger generation.
To do so, they typically invest in nice working environments, perks such as coffee and meals, flexible working hours, game rooms, and other amenities that attract data analyst talents and the younger crowd. At the end of the day, regardless of age, everyone enjoys these benefits.
Creative Freedom
As you might imagine, data analysis is not like algebra. There’s not one way to get to a solution. In fact, given the prevalence of data wrangling technology, there are almost more ways to analyze data than we can count.
In this way, the nature of data analysis is creative. In addition, because of the solitary way one analyst goes about his/her analysis, there’s a lot of freedom involved.
Ultimately, an analysts has 100% creative freedom to reach an answer. The only limitations she must respect are those of logique and data quality dimensions (LINK).
For many analysts, this dynamic is an answer to their prayers. While entering the corporate world often spells disaster for creative thinkers, data analysis roles are an intellectual island in an ocean of executers.
Intelligent Coworkers
We’ve talked about how teammates are young, which comes with a whole set of advantages.
At the same time, coworkers are (usually) of above-average intelligence. This is because they need strong fundamentals in math and logique, and need to excel in their academic fields in order to perform tasks required of them.
DISCLAIMER: this does NOT mean data analysts need a STEM or technical background. On the contrary, many high-performing analysts come from humanities, business, and even literary backgrounds.
It’s a common misconception that data analysis requires advanced math skills. The reality is it requires quick fundamental math skills — something that everyone has with just a small but consistent amount of practice.
The one caveat to this is that advanced data analysis requires strong statistical skills and theoretical knowledge. But this shouldn’t frighten anyone interested in exploring a career as a data analyst. On the contrary, it’s relatively easy to pick up advanced skills on the job.
Respect at Work
An old saying goes, “there are only three things that motivate people: sex, money, and ego.” That might be an overstatement, but most people would agree that feeling respected is a huge source of professional fulfillment. For certain people, the desire to feel respected is stronger than for others.
If respect is something you look for, data analysts are very well respected. In my opinion, this is partially linked to the association with math, the scarcity of the skill, and the value of the skill. Every department manager would like to have a data analyst provide him/her with insights, and most teams appreciate validation/challenges to their ideas.
The combination of these variables create an environment in which data analysts are highly respected.
Interdepartmental Cooperation
In the same vein as respect at work is interdepartmental cooperation. As we’ve explored, data analysis applies to nearly every aspect of an organization. This means that on many occasions data analysts have the opportunity to work on all kinds of topics.
For the curious mind, this is a huge advantage.
Access to Exclusive Data
If you have ever had access to a secret, you have it can be exciting. Now imagine having access to thousands of lines of secrets. In a word, it’s exhilarating. For those who like having a glance on exclusive information, data analysis is a great role.
At the same time, data analysts need a strong sense of control. Part of knowing the exclusive information is a strict discipline to keep it secret. Data analysts must never divulge exclusive information they learn on the job.
Access to Cutting-Edge Systems & Software
Data analysis as a profession moves very quickly. New technological advances come out each year, which means companies that value data analysis have to keep up with the market.
Data analysts, thus, benefit from being part of these companies. They have the opportunity to explore new technology on a rolling basis. In fact, this is a good metric for evaluating the value a company places on data analysts: do they use recent technology?
Good Salaries
Quite simply, data analysts make between $60k and $80k depending on the state in the US, with huge potential for growth in BI and data scientist roles, which make between $70k and $100k, and between $110k and $150k per year, respectively2.
Why you should NOT become a data analyst
As mentioned, data analyst work with data and with people. If you only like technical challenges, or only like working with people, then you might find yourself unhappy with the work.
However, you will always have the opportunity to move into roles focused technical aspects if this is important to you.
Other than that, the only reason to not become a data analyst is, simply, data doesn’t interest you.
