Data is Escaping The Data Department
A meeting at a large public-sector organization once took a different agenda entirely and lost about fifteen minutes to it, because two departments had brought different numbers for the same thing.
The revenue figures didn't reconcile. Neither did the count of active accounts, which sat on the same slide.
Two numbers, two departments, all had printouts, nobody agreeing on any of it.
Both sides were certain.
Only a couple of people in that room were from the data team. Neither of them was arguing. This was ‘business’ against ‘business’, and it wasn’t a particularly polite exchange.
What settled it was not seniority. A mid-level member of staff in that room said precisely where their figure came from, which filter she had applied, and why "active" meant one thing in the tax system and something different in marketing. They had done the work of knowing. That was all it took.
That was about 10 years ago.
I think about that meeting often because the argument has quietly spread into almost every kind of job.
I have spent over a decade in enterprise data management, and a fair amount of that time doing capacity building; training people on analytics, both inside the organisations I have worked for and as a consultant outside them.
You notice the same patterns from both sides. The tools got easier. The data became more accessible. Waiting for someone else to answer every data question became the slow option. And somewhere along the way, handing over a number stopped counting as an answer.
But there’s another shift happening that I find more interesting. Three things I keep noticing:
People Build It Themselves Now.
At the large public-sector organization, we ran on OBIEE – one of the earlier dashboarding tools – for a couple of years. Everything went through it, and that arrangement felt permanent the way arrangements do.
Then a young man joined the team, quietly obsessed with Power BI. Over one weekend, he built something that made half our standing reports look tired. The build was good. The courage to show it was better.
The question is no longer always, “Can the data team build this for me?”
Increasingly, it’s, “Can I build this myself?”
The Person Who Explains the Number Gets Invited Back.
Not necessarily the person who produced it. A friend of mine crossed into data from the business side and remains one of the best data analysts I have known; he went on to a FAANG company and has since moved on again.
What set him apart early was never technical. He could tell you why a figure had moved, who had changed it, and what you should pay attention to next. And you’d believe him. That’s the skill that travels.
People Keep Their Own Spreadsheets.
Almost everywhere I have worked, somebody maintains a file that is not official, not in their job description, and is nevertheless treated by their whole team as the source of truth. They started it because the system did not capture what they actually needed. That is data work. They rarely call it that. They rarely get credit for it.
The interesting thing isn’t that everyone is becoming a data analyst. It’s that data work is increasingly happening outside the data department.
It’s that more people are becoming responsible for understanding, questioning, and explaining data as part of their actual jobs.
If you recognise yourself in any of this, there are a few simple things you can do.
Learn visualization, not just visualization tools. Sorting a bar chart by size rather than alphabetically has rescued more presentations than any tool I know.
Write down the reporting request you dread most. That’s probably your first automation candidate, and probably your first portfolio piece.
You don’t necessarily need to leave what you already know to become better at working with data. Your domain knowledge is the hard part. You’ve already done that bit.
The next step is learning how to turn what you know into better questions, better analysis, and better decisions.
There are many ways to get there, and several organizations cover this path. Learnly Africa is one of them, through its Data Analytics Masterclass.
Kevin Ougo is a data practitioner with over a decade of experience in enterprise data management; he has spent much of that time on capacity building, training people in analytics both within the organizations he's worked for and as an independent consultant.
He helps professionals turn practical, real-world data skills into better decisions on the job.
