Elevating Data to a Profession: Why It Matters

Data is a growing trade, but is it a profession? Not yet. It is time we address this.

Data is a growing trade and a fulfilling career, but is it a profession?  I don’t think so.  Not yet.  However, I believe it's time for it to become one - this is a transformation that we, as a data community, can bring about. Interested?

Today anyone can call themselves a data professional.  There is no agreed-upon standard.  No recognised qualification.  Many data leaders, myself included, say they fell into data because they liked solving problems.  Whilst problem-solving is a great way to learn data, it leaves a lot of gaps.  

My route to CDO was through analytics and transformation.  I’d learned about visualisation, product management, data science, data engineering, cloud computing but lacked even foundational knowledge of data governance, ethics, modelling or regulations.

Now I’m not suggesting that anyone can or needs to be proficient in all these areas.  But some foundational knowledge?  That might just go a long way.

After all, a broad foundational knowledge of your domain is a pre-requisite in the established professions. 

To become an auditor, you first train in accounting and then specialise in audit.

To become a cardiologist, you first train in medicine and then specialise in cardiology.

To become a family lawyer, you first train in law and then specialise in family law.

To become a data scientist, engineer, or analyst, you first specialise in your specific area and get no foundational training in the broader data field. 

Having trained as an accountant before transitioning into data, I've experienced the benefits of a solid professional foundation firsthand.

Because of my accounting qualification, I have enough knowledge of the different accounting disciplines (tax, audit, corporate finance etc.) to easily work with teams in these areas.  There is a common language and way of doing things.  A professionally trained accountant can easily take ultimate accountability for a finance function as a CFO, they have knowledge of all the areas.

The same is not true in data.  I’ve seen the challenges in different data specialisms to collaborate.  They don’t share a common language and understanding of each others areas.  When I became a CDO I couldn’t easily take ultimate accountability for all data activities, I had too many knowledge gaps.  

The most concerning knowledge gap in data specialists is the lack of training in data ethics, principles and regulations.  

This professional knowledge is part of why we trust doctors with our health, accountants to represent our finances and lawyers to represent our legal interests.

Would you be happy to trust a doctor with no foundational training in medicine?  Could you imagine a world where doctors had no training in medical ethics?  Where there were no concepts like the Hippocratic oath?

Do you feel comfortable trusting important decisions to data models designed by people who've never been trained in data ethics or regulations?

Today it seems everyone is.  In many forums, data ethics is currently seen as an emerging area, rather than a core fundamental.  Most people that work in data have no training in data ethics.  Little awareness of practices like consequence scanning.  And, at best, they have a passing knowledge of data regulations like GDPR.  

By contrast I’m overwhelmed with communications from my accountancy body every time there is a change in accounting regulations.

Now, let's imagine a world where data is professionalised, like medicine, law, and accounting.  Would developers have put more thought into the social media algorithms that led to doom scrolling?  Would there have been fewer incidences of algorithms with racial or gender bias?  Less concern on recent AI breakthroughs?

As our reliance on data, automation, and AI intensifies, so do the risks of not professionalising data.

It's time for us to take action. Based on my conversations with CDOs and training companies, there's a strong interest in solving this. Let's work together to define an open foundational framework for data professionals. If you want to be part of this change, get in touch with me. Please leave a comment, email me (benny@datent.com), or share this article with others who might be interested. Together, we can make a difference by professionalising data.