Data analytics is a competitive and demanding field. There are definitely technical skills to master in order to succeed in the data analytics field. However, you’ll also want to be armed with certain “soft” skills and personality traits if you truly want to set yourself apart from other candidates.
After working as data analysts – and hiring others – throughout our careers, we at Skillwave feel that the very best data analysts possess the following non-technical skills and traits:
To understand why each of these soft skills plays a role, let’s illustrate how important they are to, and how often they are leveraged in, the typical life cycle of a data analytics project:
Gather Business Requirements
The first thing, before any analysis is even done, is to figure out what exactly the stakeholders need to see or expect to get from their analysis. While it is important to have some technical skills behind you, such as knowing what your tools are/are not capable of doing, it is equally important to possess a collection of soft skills in this area. Great communication skills are essential for teasing out what your clients are truly after. A systematic process (think Who, What, Where, When, Why and How), can be critical to understanding what the client actually needs. You also need to be open-minded about what the client is asking for, using your creativity to figure out how to address their concerns.
One skill that cannot be overlooked is industry savvy and experience, and it is a key reason the self-driven analyst tries to learn as much about their company (or client) as possible. Simply put, it helps you determine the end goal faster and with more accurate results in the long run. (There is nothing harder than working with a client who doesn’t know what they want or need, and these skills are critical to helping them work through that process.)
Of course, in any meeting where you are tasked with gathering business requirements and committing to what you can deliver, you’re definitely going to need both negotiation and problem-solving skills as well. (Do you think you’d be able to convince your boss or client that a pie chart is not the most effective visualization for their analysis? And what do you do if they insist upon it?)
It's worth noting that this step in the process is always important, but for larger projects, it quickly becomes critical. Generally speaking, the more effort put into this stage of the solution, the more likely it will be successful in the end. For small projects or single reports, it may just be a short email with the specific output required. For larger projects, however, possessing a systematic mindset makes it much more likely for the analyst to insist on meeting and documenting the requirements. Additionally, it's also important to get sign-off agreement from all parties before delving into the technical areas to deliver on the requirements. This process reduces the likelihood of the project failing to deliver, or needing to be rebuilt from the ground up. (It’s all about managing expectations and deliverables up front!)
As you can see, we haven’t even moved past the first step of the process to leverage our technical skills at all. It’s the analyst’s personality traits, soft skills, judgement, and working methods that are the most important.
Get Data
Once the scoping is complete, the next step is to go and get your data. And while we’ll forgive you for thinking that this is purely a technical step, we need to assure you that nothing could be further from the truth. While technical training is critically important, the reality is that you’re also going to start leveraging your analytical skills (to determine what data you need), your negotiation skills (to get access to the correct data sources in the first place), your problem-solving skills (to figure out how to work around challenges), and your creativity (to come up with alternatives where necessary).
In addition, you need to be a self-driven individual to do this, as your manager does not want you coming back to them every time you hit a minor roadblock. Sure, we’ll be there for the major issues. But we want you to come to us when you need support, not to solve the challenges we’ve given you in the first place.
Cleanse and Re-shape the Data
Again, what seems like a purely technical portion of the analysis requires a collection of soft skills you need to be truly successful. While it is entirely possible that you’ll get presented with a nice clean table of data and just be asked to prepare a simple chart, the reality is that this kind of job isn’t going to happen often. More likely you’ll end up acquiring data that needs cleansing or reshaping into a tabular format.
Often, you’ll find that getting to the ideal data source is like a puzzle, requiring a trial and error (systematic) approach, leveraging your analytical skills to determine if you’re on the correct path to success. And when you hit a wall – which you definitely will – you need to be able to sit back, clean your mental slate, and think about other approaches that you might take (leveraging both your creativity and problem-solving skills yet again). I can recall more than one instance in my career where I’ve had to walk away from an analysis after an hour of frustration, only to come back later, try a different approach, and unlock the entire puzzle in minutes.
Model and Summarize Key Statistics
The entire job of a data analyst is to turn data into information that delivers actionable insights. From a technical side, we need to understand what our data tables should look like, how to build the key mathematics behind the summary, and how to build the charts, tables, and other visuals to support our analysis. There is a lot wrapped up in there, so let’s think about what soft skills need to be leveraged to accomplish these goals…
An analytical focus is obviously required to generate the values being presented, as well as validate that they are factually correct. And it probably goes without saying that your problem-solving skills are going to be key here, as you work through the technical process of delivering on the requirements. It’s also critical to be applying all those communication skills as you deliver on the requirements to make sure that the story is being told in the most effective and human-consumable way possible – even if you aren’t dealing with humans at this stage of the project! (Supplementing those natural human communication skills with some good technical training in data visualization is highly recommended!)
On a personal note, there is something that I would like to offer at this stage which I believe sets the exceptional analyst apart from a good analyst. I truly value analysts who are self-driven and leverage a bit more creativity during this stage. Analysts who come back and say, “Hey, by the way, I was poking through the data when I was building the report and found this interesting insight…”are worth their weight in gold. These analysts help uncover things that we didn’t even think to ask about. (Some of the most valuable insights we ever discovered in one of my previous jobs came from me just “poking around” and experimenting to find better ways to display information.)
On the flip side, if you want to drive me nuts, skip that last step of checking the report you’ve built for me against the business requirements we agreed to in step 1. This gets back to that systematic process. Just like spell check is an important part of the delivery process, checking that you are actually delivering on what your client requested is critical. And this is something that a great analyst has as part of their core – I should never need to tell you that reviewing your work prior to presenting it is important. You should take pride in what you build, and it should be worthy of that pride.
Delivery and Feedback
Let’s advance to the stage where the analysis is done. You’ve checked the calculations (twice) and are sure that it is presented in the most effective way. It’s now time to deliver it to the intended audience, be that the original requestor or the audience for whom you’ve been designing it.
For the analyst, there is nothing truly technical in this part of the process at all. The report is built, the technical work is done. It’s ALL about your soft skills at this point.
It’s tempting to just give someone a report and dive right into the results. You may even feel that – if you did your job correctly – your analysis should stand on its own and not need any explanation. Sometimes, for a simple analysis, this may be true and delivery via email or an invite to a shared report will be a perfectly valid approach to delivery. However, the more complex the deliverables, the more the value of a systematic mindset and process becomes. You need to review the solution against the deliverables and validate the results with the client.
And then comes the truly terrifying stage: user feedback.
A critical factor upon delivery is going to be how open-minded the analyst is to feedback about the results. Going back to the systematic approach once again, this is where a specification document can be incredibly useful. The main reason is that it provides justification for what was presented. It also provides an opportunity for you to communicate about where the methods or results had to deviate from the original specifications based on the challenges you encountered.
Of course, the reality is that no matter how well-scoped the initial requirements were, the creativity applied by the analyst during construction won’t always meet everyone’s expectations. (Our hope is that you are exposed to constructive criticism about these issues, something we feel is more likely if you have an agreed upon specification document in hand!)
Regardless of the reason or source of the feedback, those negotiation skills are once again going to come into play as you agree to what or how to retrofit the solution.
Conclusion
While there is no doubt that a strong technical background is essential to becoming a successful data analyst, they aren’t the only skills you need. Soft skills and key personality traits play a big role. The most effective data analysts we’ve seen are creative, self-driven people – problem solvers with a flair for analytical challenges that they work through in a systematic way. They are open-minded and possess great communication skills which they use when they develop solutions and negotiate challenges with their clients. And while many already possess industry savvy, those who don’t will be motivated to dive deep into their client’s or company’s business line to understand what truly matters to them.
