Today, I’m sharing the 3 specific professional skills that every data analyst must learn to earn more in their careers, plus the online resources to learn each one.
Professional skills (also known as soft skills) are the things you do in your job that aren’t technical skills. In your job, you’ll use data to solve problems for lots of people:
- Your boss
- People outside your company
Unfortunately, most data analysts don’t realize there are professional skills that make working with others much easier.
Professional skills are the key to a successful, long-term career in data analytics.
Without these skills, here’s what your career will look like:
- Become an “order taker” and work on simple tasks only
- Never move ahead in your career
- Get passed up for promotions
There are a TON of professional skills you can focus on, but here are the ones that are most important (based on my experience of working in all sorts of data leadership roles over the past 15 years).
- Critical thinking
Here are the exact resources I recommend:
Skill #1: Collaboration
Collaboration skills are something that can be learned. You’ll use these skills every single day as you work with others.
- Meetings with your boss, clients, or coworkers
- Gathering and refining requirements for a data project
- Working across teams to get a bug fixed or new data feature completed
The great thing about learning how to collaborate is that you don’t need to know everything. It’s pretty simple once you keep the 80/20 rule in mind.
The 80/20 Rule For Collaborating With Others
- 80% of the time, actively listening to other people
- 20% of the time, you talk
Unfortunately, so many people can’t even follow this simple rule.
Here’s a real-world example: As a data analyst, you join a 30-minute meeting with a project manager to work through requirements, and identify milestones and key tasks. Spend 45 minutes actively listening to others and 15 minutes speaking.
Learn more about collaboration:
Skill # 2: Critical Thinking
Critical thinking is the ability to work through problems with creativity, curiosity, and logic. Good news: it’s a skill that you can learn by breaking it down into 3 parts:
The 3 Elements Of Critical Thinking:
- Creativity: Use data in creative ways to analyze a sales problem that nobody has thought of yet.
- Curiosity: Create “What If” scenarios to show different outcomes based on different calculations.
- Logic: Be able to back up any solution you propose or insight you come up with.
Most people don’t tell you, but applying these 3 components to a data problem is the first step to actually solving the problem.
Here’s a real-world example of how critical thinking can help solve a data problem:
A client came to me to let me know that a ton of duplicate items were being loaded into her eCommerce website. I applied some critical thinking and had some questions:
- How do we identify duplicate records?
- Which record needs to be deleted?
- Should we keep the deleted records in a backup, just in case?
- What if we delete a record for an item that has sales information?
By working through the problem creatively, with curiosity, and logic I gave 3 options:
- Option 1: analyze the data to identify the duplicate records
- Option 2: take it a step further and clean up the duplicate records
- Option 3: take it one step FURTHER and fix the root cause of the problem
Learn more about critical thinking:
- CodeBasics YouTube: How a data analyst thinks
Skill #3: Problem-solving
Data analysts solve problems with data every single day.
One of the things I love most about data analytics is solving problems that are complex and difficult. It’s a skill that can be learned, too.
6 basic types of problems to solve with data
- Predicting something
- Understanding patterns
- Putting things into categories
- Uncovering themes in a dataset
- Making connections between ideas
- Drawing attention to something unusual
Being able to apply your experience to a data analytics project and solve real-world problems is a must-have skill.
How I solved a data problem by making connections nobody else had thought of:
- The problem was related to a data migration effort. The client had to move millions of complex records in about 20 categories from one system to another.
- Every month that the records were one the old system was another few million dollars in support costs (ouch!)
- The original approach was just to start with the simplest category and work their way toward the most complex category. Not a bad strategy, since you can learn as you go.
- However, after analyzing the data, I was able to show that there were a group of categories that were relatively simple to migrate but accounted for 40% of the total volume of records that needed to be migrated!
- Simply put, they could spend the same amount of effort and complete the project faster, which saved tons of money for the company.
That’s the power of having top-notch problem-solving skills as a data analyst.
Problem-solving for data analysts:
Master these 3 professional skills to stand out from the crowd as a data analyst:
- Critical thinking