Building the perfect data team
Tue 26 Jun 2018 | Daniel Mintz
Reports have shown that 90 per cent of the data in the world today has been created in the last two years alone – with an estimated 2.5 quintillion bytes of data being created daily.
We may have copious amounts of data but capturing, storing and, most importantly, getting value from it is where the real challenge lies. Consequently, if we don’t have the people with the necessary skills to make sense of the data, then we may as well not have it at all.
It is clear the tech industry as a whole is suffering from a shortage of talented individuals who have the skills to derive business value from the explosion of data. However, this is just part of the problem. When it comes to finding data experts, business leaders have, in a rush to understand their data, focused on finding people with technical data science skills. But these data scientists often lack the subject matter expertise needed to ensure that data initiatives actually deliver business value.
Before business leaders start to build their successful team of data experts, they should understand that it is important to assemble a balanced team, who can work together collectively to make the data project work.
So if the C-suite want to hire a winning data team, what skills should they be looking for?
The first characteristic any business should be looking for in a data expert is curiosity. Someone who is interested in your business and its wider goals is likely to be of much more use than someone who is only curious about the ins and outs of algorithms.
It is easy for organisations to select candidates that have only studied computer science or maths at university. But those candidates who have studied social science subjects like economics and psychology or natural sciences like biology and physics, often are inquisitive about the world around them.
Whereas technical skills can be learned, curiosity is generally an innate quality, making picking candidates with a well-rounded education, who are keen to learn about the business, a wise move.
The next skill to look for when hiring a data team is the ability to speak both the language of data and the language of business.
A typical day of any data expert will involve meeting with different people across the organisation, understanding the business problems they are trying to solve and then translating those into actionable data questions.
People will often approach the data team with a very specific question; e.g. can I see how many people visited the site at different times on a given day? However, as they don’t have a full understanding of how the business collects and structures the data, the question is not always the right one.
A data expert needs to have both an understanding of the business context and the data available in order to progress the lines of inquiry and shed light on the business problem at hand.
Being bilingual is also essential for members of the data team as they need to be able to present their findings in a way that makes sense to key stakeholders.
Although we would like to think otherwise, if the data shows results that are too good to be true, then they probably are.
People that make the best data professionals are those who are able to question their own assumptions and the assumptions of others. The best data practitioners know that the more helpful a result is to them, the more sceptical they need to be of it. They should continually find different ways to approach a problem and test the original results to prove they are in fact correct.
Anyone who is looking to hire a data team should look for this quality. Successful data professionals are those that can dive straight into the data and gain a solid understanding of what the data is like – without someone else doing all of the preparatory work for them.
It is common for data science to be taught using only pristine sets of data, which seldom exist in the real world. Data experts need to be able to find, clean and reshape the data in order to make sense of it. Unfortunately, there isn’t an algorithm that can do this, data scientists need to get their own hands dirty.
All of the soft skills mentioned above are the fundamental building blocks of a successful team of data experts. However, that is not to say that technical skills are not important too – they are. The difficulty with defining the set of technical skills required to become a data expert is that they are constantly changing.
Technology is developing at an unprecedented rate and so having a basic understanding of analysis tools such as SQL and Excel is important, but so too is having the drive to develop and learn new skills in order to adapt to the rapidly changing data landscape.
So if you find people that are curious, bilingual, sceptical, not afraid to get their hands dirty and always willing to learn, then you will have a data team that can accomplish great things.