3 Key Programming Skills for Data Analysts

Most data analysts have programming skills in at least one language while others choose to go a non-coding route and learn tools like Tableau or Power BI exclusively (although even these become more powerful when you know how to code). 

While I’m focusing on programming skills for data analysts, these same skills are true no matter what type of platform you’re using. 

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Let’s get into 3 key programming skills for data analysts.

Skill #1: Data Cleaning and Prep

The reality of most business datasets is they’re far from clean, for a variety of reasons.

The data entry may be manual and prone to errors. People or systems may be set up to interpret data in a specific way which clashes with how data is entered….etc. 

A key step early in the data analysis process is cleaning and preparing data for analysis. Here you’re looking for places where the data may be corrupt or wrong or otherwise throw off your analysis results. 

Depending on the dataset, cleaning and prep can take a large amount of the total analysis time.

If you’re working with data that’s really messy or perhaps collected for a different purpose, there may be a significant amount of work to get it ready to analyze. 

How do you prep for this type of work?

The first step is to build your programming skills on a platform like DataCamp. Platforms like this give you a good foundation to start with and a few opportunities to test your skills. 

From there, get more practice time in on other datasets to build up these skills.

This is something you can do on your own, but if you want a more curated option, those exist as well.

I’ve partnered with Strata Scratch as a way to help you hone your skills in this area as well as the other 2 skills we’ll talk about.

Strata Scratch is a platform that lets you practice your programming skills using the types of questions companies are asking in data science - and occasionally data analytics - interviews.

There are over 500 questions in Python and SQL that let you refine your skills.

You can pick general questions or use questions that show up in interviews for companies like Facebook, Google, Airbnb, and more.

See how this works in Strata Scratch at 2:55 in the video.

If you’re interested in trying out Strata Scratch for yourself, their plans are inexpensive and there’s new content being added nearly every month.

Use code ‘careerforce15’ to get 15% off.

Skill #2: Data Segmentation and Aggregation

Most of the time, once you finish data cleaning and prepping, your next step is aggregating and/or segmenting the data. 

When it comes to aggregating, you may be looking for sums, averages, etc.

This could be over all time, all customers, and all products, or - more often - just for a specific time period, specific customer segments, or specific products.

These segmentation questions are often quite useful in taking steps towards changing the business.

See how this works in Strata Scratch at 4:55 in the video.

Skill #3: Data Exploration

Data exploration takes aggregation and segmentation to the next level.

It’s about finding interesting trends and relationships in the data that could bring value to a business. 

What can you figure out about where the business is headed?

How are specific factors or events impacting the business performance?

What areas seem most obvious to address?

See how this works in Strata Scratch at 5:45 in the video.

Check Out Strata Scratch

Don’t forget to check out Strata Scratch for yourself and use code ‘careerforce15’ to save 15%.