Michael, thank you so much for joining us.
Tell us about the work DQC is doing.
Yeah.
So DQC is a software solution that enables companies to
automatically fix their data quality issues.
So nowadays, all companies try to generate value with their
data, and the one thing that's holding them back is their
data quality.
And as a matter of fact, when you ask business executives,
more than 55% of them say that they don't trust the data in
their systems.
And with DQC, companies can automatically detect data issues
and improve or prevent them right at the source.
And this way, companies get better data for better business
and AI.
What are some specific problems you're helping companies solve?
So one problem with data quality is that you require, on the one
hand, functional business expertise.
So domain know-how, something that typically a business expert
would know.
And the second thing that you require is analytical skills,
because you need to assess hundreds of thousands if not
millions of data points.
And DQC automates and combines those two functionalities into
one software solution.
Frequent use cases we see is on
the one hand fixing product master data—for instance for
sustainability reporting—or sales contact information for
customer excellence.
And a third use case is for instance in the finance function.
And while all of these use cases are quite different, the common
denominator is that bad data is holding companies back.
And with DQC, you can fix that.
What foundation do companies need in place
to capture real value with GenAI?
Yeah, so with GenAI,
you really need a solid data foundation.
And the reason for that, if you think, for instance, of the
latest Gartner study, they prospect that roughly 30% of GenAI
projects will be abandoned next year due to unreliable data.
And if you try to do GenAI
with bad data, it's a bit like trying to run before you can walk.
It won't look pretty, and you won't get very far.
And therefore, you need a solution that actually enables
companies to solidify their data foundation.
And data is not static, so it evolves.
So it needs to automatically always stay up-to-date.
And then you're ready to scale GenAI
and generate value.
Thank you so much.