Evolution of the Data Analyst
February 16, 2021 -
Over the past 10 years, arguably one of the biggest transformations in the business world is the shift from decisions being made based on isolated data usage and “ gut instinct” to a data-driven approach where strategic decisions are based on data analysis and interpretation. Not surprising, the sheer amount of data that is now collected and analyzed lies at the heart of this repositioning. According to IDC the “2010 world created approximately 2 zettabytes” (1 zettabyte is a trillion gigabytes) SOURCE and the World Economic Forum calculated in 2020, only ten years later, that number jumped to 44 zettabytes! For context, storage for one zettabyte would fill 1,000 datacenters or about 1/5 of Manhattan.
What it meant to be data-driven ten years ago and the skills that were required to meet that goal were pretty basic and straightforward relative to today. This isn’t surprising, we’ve seen the same thing happen in almost every other space. For example, think about design. In the past, most organizations only needed one person to handle all of the creative work. Let’s call this person “Pat” – a jack of all trades, type of person. Pat had a tool like PhotoShop and with it, did whatever needed to be done. A point of sales display, a billboard, newspaper or magazine advertisement… Whatever it was, it was more likely than not one dimensional and really just slightly different shades of the same kind of work. But whenever a creative was needed everyone would turn to Pat and say, “Hey, can you do this?” and Pat would produce it. Over time, some organizations became big enough that Pat couldn’t do the job alone, so more Pats were hired. But they all worked in the same tool and they all did the same type of work, we just needed more Pats with the same skillset to get the work done.
But then things started to change. Different types of work became more prevalent, different types of creative were required such as animation and video, and you started to see a natural progression in the sophistication of both the tools being used and the skill sets of the individuals using them. Today when you walk into a creative agency you see people with many different titles using specific tools in specific roles.
It’s the same with the opportunity of being data-driven and the job Data Analyst. 10 years ago many companies had only one, if any, data analysts, or like with design, they started with one, and then brought on more, but they were all doing all of the tasks that needed to be done, including collecting and classifying the data, dealing with the relatively few technology platforms, data visualization and of course analysis. Data analysts of the past answered specific business questions such as what product or services generates the most revenue, what PPC campaigns result in the most clicks, what CTA on our website leads to the most conversions. They organize and sort data to solve problems and in many cases work with structured data from a single source.
Today, as the amount of data keeps growing and the variety and complexity of data is ever increasing, the sophistication of skills and technology required to become data-driven is vastly different. And the job of data analyst has atomized into specializations and unique roles. Each task of the old data analyst has evolved into its own specialty with it’s own tools and distinctive skill set. Today you have technical implementation specialists, data engineers, where you have all sorts of data analytics, you’ve got people who will focus on dashboarding, people who will focus on custom one off analyses. Add to this data scientists and people working with machine learning to not just answer specific questions but who formulate and test hypotheses, provide predictive modeling and work with unstructured data from multiple disparate sources.
The sophistication of skills required to be data driven as an organization today and to take advantage of the opportunity of data is vastly different than it used to be. Becoming data-driven requires all of these different types of different types of skills and it’s impossible for them all to reside in one person. Of course, people may have an understanding of the different parts, just like as individuals we have an understanding of each other, but it’s together, as a collective and through collaboration that we’re able to achieve anything.
Yes, it’s hard and rare to bring all of these skills together and that’s why a firm like Napkyn exists – it’s because we have brought these skills together and we can apply them to an organizations’ desire to be data driven in today’s world.
And don’t think the evolution is complete, we’re already starting to see hints of what the future holds with emerging roles like Chief Data Officers, Analytics Engineers and Data Quality Specialists.