The Order of Data Experts

This is the first part in a series of articles about Data Experts that aims to give insight into the world of Data. By looking closer at the work they do, I hope to create mutual understanding between Data Experts and organisations so that the potential of data can be grasped and better leveraged.

by Robbert de Kruijff, Experience Design Consultant

A Data Expert told me: “Many organisations hire Data Experts because AI solutions and Deep Learning are the technologies that will shape the future and are therefore well known, but many companies don’t know what Data Experts do or have unrealistic expectations.”

It’s because of these misunderstandings between businesses and Data Experts that I want to share insights I gathered in my talks with Data Experts. These insights come from interviews with many Data Experts from several industries, with a wide variety of skills and different approaches to the challenges of data.

But before going more into what Data Experts told me in interviews let’s take a step back and give you some context. When it comes to the buzzing topic DATA, a big challenge our design company encounters more and more is a phenomenon I like to call the “data gap”. The companies that approach us often struggle to account for the huge discrepancy between the massive amount of available data and the relatively small proportion of data they can actually use, that is, data that can be turned into business value. Many companies seem to have the feeling that they are sitting on a pot of gold (or oil, there are plenty of metaphors to data) but have no idea how to turn it into something valuable.

As Experience Designers we love (to observe) people, understand their needs, their challenges, and even their frustrations. This people-centred approach reminded me that there are always two sides to a story – on one side are the companies that approach us hoping to capitalize on the potential of data they already have. But what is the other side of the story? The answer is: the people who actually work with data and understand what can be done with it: the order of Data Experts (there is a perfectly good explanation to “the order of”, other than that it sounds pretty cool).

This is the reason why I chose to approach this challenging topic the way I did; together with my colleagues I conducted interviews with Data Experts working with data in a variety of ways. Data Scientist is only one ‘species’, which I’ll explain later. As experience designers we like to take the most truthful approach in these interviews. This means we start with certain assumptions (such as the data gap) and test them with our interviewees (Data Experts).

I strongly believe that if we come closer to really understanding the professional life of the Data Expert, know what makes them happy and in what circumstances they can be effective, the value extracted from data will increase as well. As mentioned in the introduction, I want to help facilitate a mutual understanding between Data Experts and businesses so that businesses get the most out of Data (Experts) and Data Experts get the most out of their jobs. It’s a win-win!

The first insight from my interviews regards the variety of different ‘species’ (different functions or specialisations) of Data Experts I found. Note: The order of the Data Experts is the overarching term for people who specialise in working with data. ‘Species’ are specialised data-functions, thus a category within the ‘order’ (visualised in the figure below). I want to connect these different ‘species’ to skills they have and outcomes they deliver. While writing the next part, about ‘order and species’, I could hear the beautiful voice of David Attenborough.

The Data Expert who I based the next part on works at what I would consider a Data Mature (meaning they manage to get a lot business value from data) company. This company is an online retailer that calls every part of their website (such as check-out, recommendation of products, etc.) a ‘product’ and builds teams around these products, with personnel possessing skills matched to each specific part of the webshop. He provided detailed explanations of how they approach the different roles of Data Experts.

“Data Analysts look at the available data from the past in order to find new insights”. In other words, Data Analysts are very curious. They are a researching ‘species’ who look at and analyze historical data searching for interesting patterns that may not have been noticed before. These insights could be the spark that inspires a new business development or innovation.

“As a Business Intelligence Expert you monitor data from the present and use it to build dashboards and reports in order to measure KPIs and success”. Business Intelligence Experts look at what is happening now in the context of business success. They are good at visualising (in a dashboard, a report, etc.) the right information needed at the right time for people within an organisation to be able to make better-informed decisions. They know what decision-makers need in order to make their decisions. They help to clarify business goals and know how to measure success.

“Data Scientists build models to predict the likelihood of certain events happening (for instance, through AI and Machine Learning technologies)”. An example of such an event from a Data Expert: predicting the likelihood of a consumer being happy with an offer for a phone contract using variables such as time of day, the brand of the phone, the amount of GB’s in the contract, etc.

Using their strong statistical skills Data Scientists like to build “fancy” algorithms to predict the likelihood of some event happening. With their models they can also determine if and how certain variables influence this event. Armed with this knowledge, the course of the future can be changed.

The Data Mature company (mentioned earlier) has a self-built infrastructure for collecting data. This means that nearly all the data they gather is measured and structured in a way that is optimal for their purposes so they never have to worry about data quality, having to rework data to fit their purpose or whether data is available at the right time for the right people.

From other interviews I learned that there are many other challenges beyond the way data is used (which often has to do with data quality and how it flows from one place to another). Just like any other resource: “S**t in is s**t out”. The importance of this fundamental issue was confirmed by one of the experts: “What do we need to do our work best? The answer is simple: it starts with good data, and some stuff around that”. Even more, a Data Science Advisor told me “70% of my work in supporting Data Scientists is preparing data in the right way, the rest is modeling.”

There are several ‘species’ who are real heroes when it comes to guaranteeing the quality of data and making sure it’s available at the right place and at the right time. They are different from the three previously described Data Expert ‘species’ (Data Analyst, Data Scientist, BI) because they are concerned with preparing data and have a more facilitating nature. These are Data Experts such as: Data Architects (creating warehouses to structurally save data), Data Administrators (keeping data warehouses safe, organised and available) and Data Engineers (creating streams of data to get it to the right places).

The Order of Data Experts

To wrap up, let’s look back to the starting quote, back to reality. This Data Scientist told me that it seemed organisations hire Data Scientists for the name, not to truly create something people want.

By describing the different ‘species’ of Data Experts out there I am trying to increase understanding about what is going on in the world of Data Experts. In future articles I hope to facilitate a further understanding that will help create a win-win situation for both the Data Expert and the company where they (will) work.

In the interest of of working together towards a better understanding of Data Experts, please, dear reader, don’t hesitate to comment and say what you think. If you have any questions you can always send me an e-mail: rdek[at] or check out our website.

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