Back in the 90s I worked for a company called BusinessObjects which, for those that don’t know, was an ad-hoc query tool. It was aimed at allowing the business user to run their own queries and not need to use standard reports and dashboards developed by a central data team.
I remember an early sale to British Steel which when they got their hands on the software, they discovered that they were using argon twice in the production line (at least that how I remember it). They where able to play around with the data rather than being reliant on the data team to build reports for them.
I think the world has lost its way a little as we seem to be going back to the old days of centralised data teams producing reports … it’s a shame.
Because there's a baseline of technical capability required to run your own queries, and people below that capability are more likely to produce garbage than not. It will never be "solved", because there are capability tradeoffs. In other words, if your sales people spend all their time learning to "pull and analyze" data, they will spend less time selling.
I get where you’re coming from, and in principle you’re absolutely right, asking non‑technical people to write their own queries is a recipe for chaos. But that not the world I’m describing. It’s one where a semantic layer removes the need for anyone to understand the underlying database at all. Instead of thinking in tables and joins, they think in business concepts, terms and ideas.
Once you have that semantic layer in place, you can layer on software that automatically constructs the SQL for you and Bob’s your uncle (for the record, I don’t actually have an uncle called Bob). We actually had early versions of this in the 90s with tools like BusinessObjects and English Query, though that approach faded over time.
The whole point is that the salesperson never touches a query. They don’t need SQL, they don’t need to understand joins, and they definitely don’t need to “be good at data”. They just ask normal business questions in their own language, ‘Which customers are most likely to churn next month’ and the tech handles the heavy lifting: logic, definitions, joins, filters, guardrails, all of it.
So, while your point about capability trade‑offs is valid, the ‘nirvana’ I’m describing (and yes I know it is) is something else entirely. But interestingly, we’re now seeing new AI‑driven tools emerge in this space, aiming to do exactly what those early systems promised. How successful these tools will be, remains to be seen.
Anyway, this is just my opinion for what it’s worth.
I can relate to most of what you’re saying.
Back in the 90s I worked for a company called BusinessObjects which, for those that don’t know, was an ad-hoc query tool. It was aimed at allowing the business user to run their own queries and not need to use standard reports and dashboards developed by a central data team.
I remember an early sale to British Steel which when they got their hands on the software, they discovered that they were using argon twice in the production line (at least that how I remember it). They where able to play around with the data rather than being reliant on the data team to build reports for them.
I think the world has lost its way a little as we seem to be going back to the old days of centralised data teams producing reports … it’s a shame.
Because there's a baseline of technical capability required to run your own queries, and people below that capability are more likely to produce garbage than not. It will never be "solved", because there are capability tradeoffs. In other words, if your sales people spend all their time learning to "pull and analyze" data, they will spend less time selling.
Being "good at data" isn't easy.
I get where you’re coming from, and in principle you’re absolutely right, asking non‑technical people to write their own queries is a recipe for chaos. But that not the world I’m describing. It’s one where a semantic layer removes the need for anyone to understand the underlying database at all. Instead of thinking in tables and joins, they think in business concepts, terms and ideas.
Once you have that semantic layer in place, you can layer on software that automatically constructs the SQL for you and Bob’s your uncle (for the record, I don’t actually have an uncle called Bob). We actually had early versions of this in the 90s with tools like BusinessObjects and English Query, though that approach faded over time.
The whole point is that the salesperson never touches a query. They don’t need SQL, they don’t need to understand joins, and they definitely don’t need to “be good at data”. They just ask normal business questions in their own language, ‘Which customers are most likely to churn next month’ and the tech handles the heavy lifting: logic, definitions, joins, filters, guardrails, all of it.
So, while your point about capability trade‑offs is valid, the ‘nirvana’ I’m describing (and yes I know it is) is something else entirely. But interestingly, we’re now seeing new AI‑driven tools emerge in this space, aiming to do exactly what those early systems promised. How successful these tools will be, remains to be seen.
Anyway, this is just my opinion for what it’s worth.