Top 5 Data Analyst Skills Needed

1. Math / Statistics

The first skill you need are math or statistical skills.

Whether you’ve got a degree or you’ve gone through training, you really need to have a solid foundation here.

While there are lots of different programs you’ll use as an analyst, at the end of the day, you need to understand the logic behind them.

That’s why you’re being paid.

Anyone can use a system, but you’re really bringing the expertise of how it works behind the scenes.

So have a solid foundation in regression analysis, in predictive tools, and you can study these on your own.

It’s fantastic if you have a degree. It will probably help you get a job faster, but you can also learn a lot of this online for free.

Or pick up an old statistics textbook and read that, practice what’s in there.

You’ll grow your skills and really stand out in this area. 

2. Programming

The next skill you’ll need as a data analyst or data scientist are some sort of programming skills.

This is really going to range depending on what the exact position is, and certainly in a data science role, you’ll need a lot more programming skills than in an analyst role.

There’s SAS, which is used primarily in the medical industry and by a fair number of large companies, so that’s a definite option. 

The two most popular programming languages are Python and R.

Both of these should be fairly cheap or free for you to learn. 

There’s great online training from platforms like DataCamp.

At the very least, practicing some SQL can definitely help. It shows you know how to talk in the programming languages, and you know how to take a problem, work through it, and at the end of it come out with a result that provides some benefit. 

Tailor the language you’re learning, especially if you’re focused on a new one, based on the type of companies you want to be hired at. If you’re going into the medical industry, definitely have SAS.

With other industries, any of these are great, and you can probably find out which companies are using different systems that are out there, whether it’s Python, R, SAS, or one of the many other options.

Most of them get involved in conferences or write papers, they send people from their teams to the conferences or to write papers or speak on them.

Do a little looking, you’ll be able to find out the company you want to get hired at what they’re using. 

No code analytics are also becoming very popular.

3. Problem Solving Skills

The third skill you’re going to need - and for me this may be the top skill that any analyst needs - is problem solving skills.

I can work with a new analyst who doesn’t know a software or programming language.

I can’t work with an analyst who has all of the math background, but none of the practical application.

In my view, 90% of analytics is knowing which question to ask. 

If you’re asking the wrong question, you’re probably going to find an answer, but it may not be helpful.

Think about thinking through logically different problems that you encounter.  

You almost need to look at what solution you’re going for, where you are, and what are the steps you need to get there.

A lot of this is like doing a math proof. You take the things you know to get to the things that you don’t know.

Those math skills will come in handy, but overall, how do you go about solving problems? 

The beauty of knowing how you’re going to solve the problem or knowing your approach is if you don’t know how to program that specific thing.

Once you have something to look for, there’s probably someone else that’s faced that problem that you can already find the answer online or you can go to one of the many forums and groups or different experts or the company themselves that puts out the software and ask them, “How do I do this specific thing?” 

I’ve found people are extremely willing to help, and since a lot of us analysts are really are kind of enjoying nerding out on the math side and the problem solving side, you’ll definitely find someone who wants to give you a hand. 

Learn to think like an analyst.

4. Data Visualization

My 4th out of the top 5 skills for data analysts is data visualization.

This is becoming more the expectation than the exception.

It used to be relatively rare, or normal at least to use excel for visualization, and now it’s really popular.

Think about everything you see online. Tons of stuff is visual.

A lot of people who don’t understand the data and the science part of what you’re talking about may understand a good visual.

Actually, if you’re doing a good job they will understand a good visual.

The baseline to get started if you don’t have skills here is use Excel. There are lot of different options here just in the native tool, or Google Sheets you can try something like that.

Take different data sets. Start making different graphs. Do bar charts, line charts, do combinations.

See how simply that you can tell the story.

It’s really difficult to take a complicated topic and make it simple, and that’s really what you’re being asked to do when you visualize data. 

Beyond that, there are again plenty of other visualization platforms. 

You could learn Power BI or Tableau. 

If you’re really into programming, you don’t need any of these. You’ll just be able to code any of these visualizations, and that’s great too.

SAS again if you’re working for a large company, they’ve got some fantastic tools, both with their SAS visual analytics and within some of the other tools that they have.

Take some time learning how to visualize data.

The way I like to look at it is, “What would I do that would make my mom understand this?”

My mom doesn’t necessarily understand analytics. She’s smart, but doesn't have a deep knowledge of analytics so if I can communicate information about topics that are really complicated in a clear way that she understands then I've done my job as an analyst. 

When you’re in the business, chances are there are going to be some other analysts around, but you’re going to be dealing with a lot of people that have a high level knowledge of the subject, especially as things go further up the chain.

If you have things going up to the CEO or C level in general, they’re going to have some idea of what’s going on, but you need to really break it down, make it super clear for them to understand. They want to know both what’s going on and also the impact.

What’s the insight they should take away?

Great visualizations respond to those needs. 

They communicate the insight they need to know from the data, and what the conclusion is that they should draw so that they can take smart, well informed actions that affect the rest of the business. 

5. Communication Skills

The 5th skill you’ll need to really be an excellent analyst is communication skills.

I think this is one of the top reasons why my career grew as fast as it did.

Especially if you’re looking to move into managerial roles, or even higher levels within a company, you need to know how to communicate.

It’s really not that much different than a data visualization, but this piece I’m talking about not just the graphics, but how do you talk with people, how well are you able to write and articulate what you need to say? This is super important.

You need to be able to be clear with people.

Work on your communication skills.

Make sure you’re able to break down technical information really simply and explain it.

You can be the most fantastic technical programmer.

You could be the most skilled person in the world, and if you can’t communicate it, it’s really going to hurt your career.

Those are my top five areas for data analysts to have skills in. Let's get into a bonus tip now.

Bonus Tip

This is the tip that will really make you stand out, especially if you’re applying for a job, and you’re on par with other candidates. 

Know the industry. 

You can be amazing technically, you can have good communication skills, you can have great math skills, but knowing the industry makes you really valuable and saves a lot of training time for people.

You’re more likely to be able to do effective analysis if you understand what’s going on.

Know the competitors.

Know the type of work that’s going on.

If you’re in the automotive industry, know how horsepower relates to torque or engine size.

If you’re in the software world, know how processing power relates to other factors.

All of these things help you become much more effective as an analyst.

What I’ve found is when people don’t know the industry,

1. It takes them a while to be effective
2. They also usually draw conclusions that they are so proud of and find so amazing, and are completely unrelated to the business because they’re connecting things we already know are directly connected. 

Knowing the industry will really make you stand out, especially if you’re going for a particular job or want to be in a particular industry in general.