WEBVTT

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Michael, thank you so much for
joining us.

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Tell us about the work
DQC is doing.

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Yeah.

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So DQC is a software solution
that enables companies to

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automatically fix their data
quality issues.

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So nowadays, all companies try
to generate value with their

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data, and the one thing that's
holding them back is their

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data quality.

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And as a matter of fact, when
you ask business executives,

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more than 55% of them say that
they don't trust the data in

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their systems.

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And with DQC, companies can
automatically detect data issues

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and improve or prevent them
right at the source.

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And this way, companies get
better data for better business

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and AI.

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What are some specific problems
you're helping companies solve?

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So one problem with data quality
is that you require, on the one

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hand, functional business
expertise.

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So domain know-how, something
that typically a business expert

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would know.

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And the second thing that you
require is analytical skills,

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because you need to assess
hundreds of thousands if not

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millions of data points.

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And DQC automates and combines
those two functionalities into

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one software solution.

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Frequent use cases we see is on

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the one hand fixing product
master data—for instance for

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sustainability reporting—or
sales contact information for

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customer excellence.

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And a third use case is for
instance in the finance function.

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And while all of these use cases
are quite different, the common

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denominator is that bad data is
holding companies back.

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And with DQC, you can fix that.

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What foundation do companies
need in place

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to capture real value
with GenAI?

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Yeah, so with GenAI,

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you really need a solid
data foundation.

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And the reason for that, if you
think, for instance, of the

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latest Gartner study, they
prospect that roughly 30% of GenAI

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projects will be abandoned next
year due to unreliable data.

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And if you try to do GenAI

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with bad data, it's a bit like
trying to run before you can walk.

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It won't look pretty, and you
won't get very far.

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And therefore, you need a
solution that actually enables

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companies to solidify their
data foundation.

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And data is not static,
so it evolves.

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So it needs to automatically
always stay up-to-date.

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And then you're ready
to scale GenAI

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and generate value.

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Thank you so much.