7 In-Demand Skills for Data Analysts

Wondering how to improve your data analysis skills, and whether it will be worth your while to do so? You are certainly not alone in that.

Businesses are generating more data than ever before, and it’s increasing every year. However, in order to gain anything from the process, this valuable data has to be quantified and analysed so it can be put to good use.

This is one of the reasons why the analysis and synthesis of data is such a fast-growing career segment, and why employees with data skills are in such high demand.

But what skills does a data analyst need, exactly? This is a fair question, since many analyst roles are rather nuanced. However, there are certain skills that are vital in analyst careers across the board. These include the following:

1. Clear communication

Truly talented data analysts straddle an interesting divide – these are the ‘numbers people’ who are able to communicate complex ideas in understandable ways to both technical and non-technical audiences. After all, your insights are only valuable when your audience is able to understand it and make use of it. The trick lies in taking intricate ideas and translating them into coherent documents and/or reports.

2. Data presentation & visualisation skills

Data presentation and visualisation goes hand-in-hand with communication. This is the tool you use to make your data understandable. Being able to think visually and create attractive presentations makes a big difference. The better an analyst is at ‘framing’ their insights so it makes sense for their audience, the more valuable their contribution will be.

3. Critical thinking

Your answers are only as good as the questions you ask. Data analysts need to figure out what questions they should be asking, and this calls for critical thinking. When you are able to think beyond the obvious and that which already exists, new connections are made and parallels are drawn. This is when data magic happens.

4. Attention to detail

Accuracy is non-negotiable when it comes to data analytics. This is why analysts have to be very good at meticulous analysis, interpretations, and evaluations of data sets.

5. Math skills

Similarly, an above-average faculty to process numerical data sets analysts apart in their field. To a certain extent, this is an innate skill, but it can also be honed through practice. Once you are actively working in the analytics field, your day-to-day duties and activities will also help you to zero in on these skills in particular.

6. An understanding of machine learning

Artificial intelligence and machine learning are emerging fields that dovetail beautifully with data analytics. If you really want to stay ahead of the curve, it is recommended to look into tools, such as Orange (an open-source data visualization, machine learning and data mining toolkit) once you have your statistical programming skills down pat. It’s a good intro into ML and will allow you to think outside of the box when it comes to this data science field.

7. Technical skills & tools

There are certain technical skills and tools every budding and seasoned data analyst should have at their disposal. This includes:

  • Excel. So much more than just a spreadsheet generator, this platform actually has a lot of analytical power when wielded correctly. It has limitations when it comes to larger data sets, which is why successful analysts learn a statistical programming language to bolster their skill sets, but it still has its place.
  • SQL. Structured Query Language is an industry benchmark database language that is used to manage and store data and relate to multiple databases. For instance, this is used by online megastores like Amazon to generate recommendations on products that you might be interested in based on purchases you’ve made before.
  • R and Python are the next step up from SQL. It is used to take big data sets and perform advanced analyses and predictive analytics based on the contents thereof. The great thing about these languages is that they are freely available on open-source platforms.

Final Thoughts

The skills a data analyst needs include clear communication, critical thinking, attention to detail, math skills and data presentation skills, as well as an understanding of ML, and proficiency in tools and languages like R, Python and SQL.

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The skills required for a career in data science or data analysis include clear communication, critical thinking, attention to detail, math skills and data presentation skills. Analysts also need to be up to date with technical skills and tools. With these proficiencies at your disposal, a thriving career in data analysis awaits.

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