FAQs: How to Enter the Data & Analytics Field

I love talking about my experience working in data & analytics, and how I transitioned from an unrelated career (marketing). As a result, I get asked a lot of questions about how I made the transition, how to land a job in this field, if a master's degree is necessary or worth it, etc etc etc.

Here is my first compilation of some of my most frequently asked questions, along with my answers. This post focuses on how to prepare to enter the field — what kind of skills, education, training, etc, you should get.

How did you land your first analytics job?

My journey into analytics wasn’t planned. It was also gradual. It wasn’t one big thing that paid off in a new job. Rather, it was years and years of seeing opportunities to use data in my previous roles in marketing, and trying to learn as much as I could on my own to get as much value out of the data, and then sharing my insights. Eventually, that was recognized, and during a team reorganization, I was moved into my first analytics role.

So, if you’re working in something that doesn’t have a variation of “data” or “analytics” in the title, but you want to transition, look for opportunities in your current role to analyze data. Even if no one is asking you to analyze it, or it’s not part of your job description. This is easier to do if you’re working in any type of business, corporate, research, administrative role.

What are the common skills needed for an analytics job?

Usually, the common expectations are

  • Basic statistical knowledge, usually what you would cover in a statistics 101 course in college.
  • Being comfortable enough with SQL that you can use it on your own (and also pass a SQL test or quiz during an interview).
  • Excel is also an expected skill, but it’s always assumed you know it, so it’s often not tested during an interview. But it’s likely that you’ll use Excel a lot, especially if the team doesn’t use Python or R.

Additional skills that are required in some places and nice-to-haves that can open more doors at others:

  • Tableau or PowerBI or a similar data visualization tool
  • Python or R, specifically how to read in a CSV or other data source into a data frame or data table, and how to clean, aggregate, explore, and visualize the data.

There are also industry-specific tools that are good to know or can help you stand out. For marketing or any web-based analytics roles, knowing a web analytics platform like Google Analytics or Adobe Analytics can help. For marketing or sales or customer-based analytics roles, knowing SalesForce or another CRM tool can open doors.

Finally, there are a lot of transferable skills that you can learn in another job that will be very beneficial:

  • Communication: Can you distill complex ideas into clear, easy-to-understand language that your audience understands?
  • Problem Solving: As an analyst, your job is to answer questions and solve problems. Sometimes you are expected to be the one to identity those problems or questions.
  • Collaboration: You will be working with stakeholders to answer their questions, and often working with or need to rely on other analysts or technical folks. Can you work well with others?
  • Project Management: Can you scope your work, get your stakeholders to agree on a deliverable/outcome, and finish your work in an agreed-upon timeline?

Do I need a college degree, and if so, what major?

For experienced candidates, often no one cares what you have a degree in, or in some cases if you have a degree at all. So if you are able to get experience on the job, even if you title/job description doesn’t include data analysis, that will matter more than degree.

But for entry-level candidates with little to no other work experience, the most common college degrees listed on job descriptions are statistics, math, computer science, economics, business.

For data analyst jobs, a master's degree is not necessary, although sometimes it will be listed under “preferred qualifications.” This could open more doors, especially if your undergraduate degree is not in a STEM subject or if you want a more advanced analytics role or to pursue data science or machine learning, or if you want to work for a competitive company that is flooded with job applications.

Are there certificates that can help you get a job as a data analyst?

No, certificates don’t really matter in this field. Listing them on your resume won’t make a difference. There is no consensus over which certificates are good, most hiring managers and recruiters aren’t familiar with them or what they teach.

However, if you have skill gaps and feel that a certificate program can help you close those skill gaps, then it can still be worth doing the certificate to gain those skills. But what will make a difference is showing that you know those skills — so do a project on your own if you don’t have a job where you can apply those skills.

What kind of analytics projects should I do?

You want to show that you can

  1. Identify a problem
  2. Find an appropriate data set
  3. Clean, aggregate, explore the data
  4. Come to a conclusion (hopefully that answers or solves part 1), summarize your insights, and make recommendations
  5. Put this into some kind of presentable deliverable (such as PowerPoint, Tableau or PowerBI dashboard, Jupyter Notebook, R Markdown, or even a well-formatted Excel or Google Spreadsheet).

Projects should focus more on solving a problem and delivering value than on using the fanciest or most advanced tool.

I’ve applied to hundreds of data analyst jobs with no response and/or no offers. What am I doing wrong?

Are you networking? Usually, this is the biggest gap I see in someone’s approach to job searching.

Entry-level roles in data & analytics are flooded with applicants, especially at tech companies. The unfortunate reality is your resume might not even get looked at by a human, that’s how many applications they get. I heard one FAANG recruiter say they sometimes get 18,000 resumes for 1 opening.

Referrals are a great way to get your resume to stand out, so start spending time networking and expanding your professional network. There are lots of online communities for data & analytics that you can start with. Additionally, your network is a great way to learn which companies and industries are hiring, especially ones you’ve never heard of (and it’s likely not many folks have, so they get fewer applications), and which companies will hire entry-level folks.

Additionally, don’t just target the impressive companies everyone else is targeting. Lots of companies and less exciting industries need data analysts, and they don’t get nearly as many applications. So also look at industries like insurance, real estate, utilities, and industrial supplies, for example. I’ve also noticed a lot of consulting firms — beyond just the Big 4 — are willing to hire new grads. So look for smaller or niche consulting firms in your city.

Finally, lots of folks broke into data & analytics via another path. For me, it was marketing. I’ve known others who worked in finance, research, software engineering, government administration, and other fields, before transitioning to data & analytics.

What other questions do you have about breaking into data & analytics?

More Resources

Check out the rest of my data analytics & career resources.

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Data Scientist in Product Analytics in Tech. Career Changer from Marketing.

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Maggie @DataStoryteller

Maggie @DataStoryteller

Data Scientist in Product Analytics in Tech. Career Changer from Marketing.

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