>> From Orlando, Florida, it's theCUBE.
Covering SAP SAPPHIRE NOW, 2018,
brought to you by NetApp.
>> Welcome to theCUBE.
I'm Lisa Martin with Kieth Townsend
and we are in Orlando, Florida at SAP SAPPHIRE NOW 2018.
We're in the NetApp booth, really cool.
SAP SAPPHIRE is an enormous event.
This is the 25th year they've been doing it
and it's been really interesting to learn, Keith,
about SAP and how they have really transformed,
and one of the things that's critical
is their partner ecosystem.
So we're excited to welcome back to theCUBE a CUBE alumni,
Paul Young, who is the director of SAP Google Market
from Google Cloud platform.
Paul, it's nice to see you. >> Well, thanks.
>> So what is the current news with Google and SAP?
>> So, I think we're making a major push into the SAP market.
I think yesterday's announcements are,
we obviously have our four terabyte HANA server online,
but we also brought up capacity all the way
up to 20 terabytes, so we basically handle pretty much
all of the customer base at this point.
So on the one hand that's good.
There is, however, a lot of other stuff we're doing
in the AI space, in the joint engineering space with SAP,
and a lot of work we're doing making it a lot easier
for SAP customers to adopt the Cloud.
And beyond just what's happening
a lot in the market right now,
which is 80% of the customers who move
an SAP system to the Cloud
just do straight lift and shift,
and so there's no form of momentum with that.
It's just ticking box, you're in the Cloud.
We're doing a ton of work in engineering
on our own and with SAP right now to make that
a much more valuable journey for the customers
so, yeah, I don't wake up in the morning at Google
and think, what am I gonna do today?
There's a lot of stuff going on.
>> So, Paul, let's not be shy.
We've had you on theCUBE before, and you're an SAP alum,
and as you look out at the hyperscalers,
the big cloud providers, SAP, more or less,
has a reference architecture
for how to do SAP in a hyperscaler cloud.
But it's not just about that base capability.
When I talk to my phone, I love asking Google questions.
When I look at capabilities like AI and tensor flow
and machine learning, that gets me excited just in general.
As you looked out at the hyperscalers,
what excited you about Google in specific?
When you were at SAP you worked for all three.
So what's so exciting about Google?
>> I joke internally.
I was a customer of SAP's for seven years.
I did 20 years at SAP,
and then woke up one morning and decided to go to Google.
I get this question a lot.
My conversation always is
it wasn't based on the cafeteria food.
(Keith laughs) It's okay, right?
There are other things that drove me across.
And seriously, because in my last role at SAP
I was working with all three of the hyperscalers
and one of the questions I always got from SAP people
is, "Well, they're all just the same, right?"
And when you actually work with them,
you discover they are different,
and that's no disrespect to anyone,
but they approach the world differently,
they all have different business models,
and the Google thing that really put me is the engineering
and the future focus, which is tremendous.
The stuff that Google could do was immense.
I'll jump forwards to the future and then we'll come back.
If you look at the advancements Google is making
in AI and machine learning, all of this stuff,
reorder Google IO with the custom built
test full computers that can just do amazing performance.
Great on it's own, but it's gotta be applied.
So as an example, actually we built with Deloitte,
Deloitte used to do the demonstration for it,
but just to give you an example
of where we think the future is we built a model
in AI where we basically took invoices
and we taught the AI system to do data entry in SAP.
So that's not an interface.
We didn't say, "Hey, here's an invoice
"and here's all the fields,"
and we map them all across, and
"Here's ETL, and here's all the things we do," right?
And here's all that interface mapping.
We literally said, "Imagine you're an AP processor.
"How do you enter an invoice?"
And you give it data, and you give it invoices,
and it spends a lot of time doing really stupid things,
trying to put addresses in the number fields
and everything else, and then suddenly it works out
how to enter an invoice.
And at that point it knows how to enter an invoice,
and then what you do is you give it more and more invoices,
and more and more different structures,
and it learns what an invoice is,
and it learns how to process that,
and then suddenly it can do complete data entry.
So we built that as a model.
This is the sort of thing Google does
just to test the limits.
Deloitte came along and said,
"Well, that's really cool.
"Could we actually take it and run it as a product?"
And so Deloitte now has that and they're engineering it
further out where literally you can give it any invoice.
It's not OCR, it will look at the invoice
and it will work out that it is an invoice,
where all the bits you need are from it.
It will then work out how you would do data entry
on that into and SAP system, and it will enter the invoice.
That's a future world where, I know SAP has already
launched AI around doing three-way match.
Interesting.
We're talking about a future world where
your entire cost payable department is a Gmail inbox
where they mail you invoices that you've never seen before
but were able to understand what a vendor is,
guarantees it's a vendor, guarantee it's not fraud checked,
and do the data entry completely automatically.
That is a massive new world.
And that's just a tiny little bit
of what we can do at Google.
We have a demo running on the booth
where we have TensorFlow looking at,
you're ex-pharmaceuticals, right?
We have a demo running on the booth
which is a replica of some
that we're actually running at customers,
where we have a camera reading
pharmaceutical boxes as they go past.
They're painkillers in this case.
But it doesn't just look at the box
and say I count one box.
It reads the text on the box
and it reads the text on the box
because it knows from SAP
what's supposed to be manufactured,
and it comes back and says,
well, am I putting double-strength pills
in single-strength boxes?
Is this box legal?
Have I been sent the correct box?
Is the packaging correct?
It also knows what a good box looks like,
and it learns what a damaged box looks like,
a damaged package looks like,
and it knows how to reject them.
And again, that level of technology where we can monitor
all of your production lines and give you guaranteed quality
in pharmaceuticals anywhere else,
tell me six months ago anyone even imagined
that was possible.
We're doing that right now.
That ability to work with SAP,
because it's all integrated with SAP.
We're doing a deep level of evolution.
That ability to deliver that sort of capability
at the speed we deliver it at is world-changing.
>> Wow.
One of the things that I just kept imagining
as you were going through the description of the invoicing,
I actually was on a run the other day.
I'm a small business owner and these things are troublesome.
You get in an invoice,
and I'm thinking now I've gotta deal with,
my wife does the payable accounts receivable,
I'm like, "There has to be a way to automate."
But then I thought about just those challenges,
you get one person sends the invoice
that the invoice is at the bottom right hand corner,
or the invoice number is on the bottom
right hand corner, the amount due et cetera, et cetera,
just really silly questions that AI machine learning
should be able to deal with.
Bill McDermott yesterday on stage says
that AI should augment human capability,
and that's a great example of how AI
augments human capability.
>> And in the AP example, it doesn't do 100% correct
all the time.
It knows when it's wrong.
In the example Deloitte runs,
your receipt comes up and says,
the date's wrong here, I need to fix it.
So it's taken the menial work out of the process,
and it's let people really add value in,
but it's also a great example of the Cloud at work
and what it's supposed to do.
And again, if all you do is take visual SAP
and drop it in the Cloud,
you're just running it in a different place.
If you get to a world where with Google,
we don't expose your data to everybody else,
but we understand what the world's invoices look like,
and we have that knowledge, and we make the entire world
more efficient by having the model know how to work.
That's a radically better place.
There's just never been that value problem before.
It's an incredibly exciting thing
to wake up in the morning and think that's what we do.
>> So, Lisa, in the industry we have this term
that data has gravity, and I think it's fair to say
after this week we can say that processing
technology compute has gravity.
We had another guest on that says
that they use a process and a technology and solution
and one customer works out fine,
and another customer, not the same results.
It's this complexity, it's this kinda gushy part
of technology that is just not easy
to apply across companies.
>> So the other part really quickly that I want to talk about
is this isn't just about AI,
it's not just about the future.
Like I say, I'm a long-term SAP customer.
I've worked with a lot of customers.
Everybody wants to get to the cool bit,
and though I always used to joke internally
everybody wants to eat candy.
They've gotta eat vegetables first.
And so we're gonna get you across--
>> Or making candy to vegetables.
>> Whichever way, you've gotta eat both at some point, right?
So just getting customers into the Cloud
becomes one of the challenges.
It's one of the other areas
where we're really applying engineering.
Three weeks ago we bought Velostrata, as an example.
Velostrata is an amazing company.
What Velostrata does basically
is that it's a plug-in to VMware.
You drop it in to VMware
and it watches your SAP systems running.
It profiles them and it works out what size capacity
you're gonna need in the Cloud.
At the point where it's then got enough information
it will basically ping you and say,
hey, I now have another issue.
Do you want exactly the same performance
at the lowest price in the Cloud,
or do you want better performance?
Here's two configurations.
Pick the one you want,
give it your Google user ID and password.
It will build the security, build the application servers,
and begin a migration for you automatically.
Depending on the timing, depending on the size of the box,
between 30 minutes and two hours later,
you will have a running version
of your SAP system in the Cloud.
Never been done before at that speed and performance.
The way it works, basically it's a little bit of magic,
but it knows what the minimum amount of data
we need to ship across through an SAP,
it knows where all the data is hidden
on the box on the disk that SAP needs to run.
And it just ships that first,
and then it fills in the gaps afterwards.
The repair mechanism.
So from there, on the one hand you could do lift and shift,
but frankly our competitors have been using it
to do lift and shift in the past.
And so it opens up a ton of potential.
For a bunch of customers we can replicate
their production boxes in realtime and give them
30 second RPO or RTO in high availability, like that.
Done.
But inside that I can now take that replicated image
and I can now run augments on that,
I can run test on it, I can run QE rebuilds,
where because of the Google pricing model
you don't pay me in advance.
You pay me in arrears for only
the computer time that you used.
So you wanted a QA system, you've got two days worth
of work to rebuild it, don't chuck it into your QA system.
Pay me for two days, rebuild it, and you're done.
Or, we've integrated it directly into the SAP
operating tools, so you can pipe across your system to us
and we will immediately do a test upgrade for you
into SR HANA, or ECS lackey,
or BW on HANA, or whatever you want.
I have a customer in Canada who really
jumped from ECC 6 and SRM 5 to SR HANA,
used an earlier version of the tools in 72 hours,
with a lot of gaps and looking in between.
We reckon we're gonna crush that down to under 24 hours.
So under 24 hours you can literally click on an SAP server
and we will not just bring you to the Cloud,
but we will upgrade you all the way to the latest version.
And we have all the components.
We've done it, and we're pushing that through.
And so what we're doing now is taking the hard work
and automating that so that we can
get to the really cool stuff in the AI side.
Again, this is where all the hyperscalers
host the SAP systems.
We wanna do something that's better than that.
We wanna make it easy to get there,
but we know that in order to justify what you do,
we're all in a seven year roadmap test with OR HANA,
so we wanna make it really easy to do that,
and we wanna make it incredibly easy to add in AI
and all the technologies along the way.
That's at a pricing model that nobody will beat.
That's a pretty cool place to be.
I'm mighty glad to be at Google Cloud.
>> I can tell by your energy.
So ease of use, everybody wants that.
You talked about just the example of invoices,
how they can vary so dramatically,
and whether you're a small business owner
to a large enterprise, there's so much complexity.
In fact, that was one of the things that was talked about
I think it was this morning, yeah, when Hasso Plattner
was even talking about naming conventions,
and how customers were starting to get confused
with all of the different acquisitions SAP has done.
So AI, what Google is doing with AI on SAP
sounds like a huge differentiator.
So tell us, as we wrap up here, what makes, in a nutshell,
Google different than the other hyperscalers
that SAP partners with, and specifically,
what excites you about going to market with SAP?
>> At the base level, Google's just
on a different scale from everybody.
We are effectively 25% of the Internet.
If you look at our own assets,
we own Dark Fiber or this equivalent to about four times
the entire capacity of the internet.
So my ability to deliver to those customers at scale
and at performance levels, just unchallenged in the space.
Google clearly has excelled in a lot of different areas,
it's incredibly exciting to bring that to SAP
and carry it through, but you're right
that the value added ultimately isn't just the,
"Hey, I can run you and I can run you better."
The value added is, so March we announced
direct integration with HANA and Google Bigquery.
We haven't even talked about Bigquery.
Massive data sets that you can out bridge to HANA.
If you're a retailer, just as one last example,
I can now join all the ad tech data Google has,
so I can tell you all the ads
you're currently running on Google,
what's being watched, what's being viewed,
anonymized in clusters, so you can't tell
they're individual consumers, but I know that data,
and directly load it to BigQuery, and I can join it to SAP.
So I can now say,
"You are advertising in this area that's being clicked on,
"but I know you don't have the inventory
"to actually support the advertising,
"so I want you to move advertising somewhere else.
And so I can do that manually right now.
When I add an AI to that, the potential is incredible.
We've only just started.
Next time I'm on theCUBE, we'll see where we're at.
But it's a fun place to be.
>> Oh, yeah. >> It sounds like it.
>> Speaking of next time, you guys
have a conference coming up with Google.
>> Next is coming up at the end of July.
Yeah, we have a lot of announcements
through probably the rest of the year.
There's a lot of stuff going on
as we come to massive scale in SAP space.
So yeah, anyone who's interested in this stuff,
especially, even if you're just interested in AI stuff,
Google Next is the place to be, so yeah.
>> It sounds like it.
I'm expecting some big things from that,
based on what you talked about and how enthusiastic you are
about being at Google.
Paul, thanks so much for joining Keith and me
back on theCUBE,
and we look forward to talking to you again.
>> Thanks.
>> Thank you for watching theCUBE.
Lisa Martin with Keith Townsend at SAP SAPPHIRE 2018,
thanks for watching.