STEPHANIE WONG: OK, lots of great news
coming at you through the Data Cloud Summit
across data analytics, data management,
artificial intelligence, and business intelligence.
Today, I have on the show Bruno Aziza,
the Head of Data Analytics at Google,
to take us through the announcements
and how they can help you.
Bruno, welcome to the show today.
BRUNO AZIZA: Thanks for having me, Stephanie.
STEPHANIE WONG: Bruno, you're fairly new to Google,
but you are not new to data analytics.
You come to us from companies like Microsoft, Oracle,
BusinessObjects, and many other data analytics
startups that you helped launch.
So tell us about the context of today's Data Summit
announcements.
BRUNO AZIZA: Well, as you know, at Google, we
are obsessed about customer feedback,
and we've been really laser-focused on delivering
innovation that helps them accelerate
digital transformation and data-powered innovation.
And at the event, you're going to hear from great customers.
They're talking about how they got it done.
So enterprise leaders, like Equifax, and Deutsche Bank,
and KeyBank, and Rackspace, and Zebra Technologies,
as well as digital natives like PayPal, Wayfair, Workday,
Electronic Arts, and many, many more.
And these customers have all told us the same thing, that
to succeed, they really need a unified data and analytics
platform that is open, intelligent, and trusted.
And by open here, I mean open to multiple clouds,
open to our thriving partner ecosystem,
and open to the world of open source
so that customers can innovate on their own terms
with maximum optionality and portability.
So you'll hear, for instance, about BigQuery Omni for Azure.
You'll hear about Looker, hosted on Microsoft Azure,
and a new service around data analytics sharing called
Analytics Hub.
We also have talked to customers about the critical role
of artificial intelligence in their ability
to gain value out of data faster, gain insights faster,
and so today, you will hear about a product called
Dataplex.
This is our intelligent data fabric solution.
And then finally, we believe in meeting customers
where they are, so you'll also hear about a new service called
Datastream.
This is a serverless change data capture
and replication service.
It allows customers to deliver change data streams
from their Oracle and MySQL databases
into Google Cloud Services, like think BigQuery, and Cloud
SQL, Google Cloud Storage, and Spanner.
So you're right, lots going on, lots of new services,
and new innovation, and new programs
being introduced this week across the database, analytics,
BI, and AI.
In fact, last time I counted, I think
there was something like 13 or 15 new services and programs
that we're introducing just this week.
STEPHANIE WONG: Wow, so, OK, can you
give us a little bit of a sneak peek and dive
into those announcements?
BRUNO AZIZA: Yeah, so the first one I'm really excited about,
and I think will bring tremendous value to customers,
is a new service called Dataplex.
So Dataplex is our intelligent data fabric service.
Now, we know that the customers' environments and the data
environment has become really diverse, and sophisticated,
and very distributed.
In fact, customers have data everywhere.
They have it in their data lakes,
in their data warehouse, in their database,
in their data marts.
Sometimes they have it on-premise as well as
across multiple clouds.
And each of the systems designed to manage
the metadata, the data quality, and security and compliance,
are unique.
And managing that situation can be an operational nightmare
because organizations find sometimes they
have to move the data.
They have to replicate it.
They have their homegrown system to manage their various silos.
And the minute the data is obsolete,
sometimes even the second the data is obsolete,
now, everything's got to change.
And so we believe that organizations
should have the freedom to choose the best place to store
their data based on price and performance considerations
to make it available to their people
without compromising security and governance.
And that's why we built Dataplex.
Now, think about Dataplex as three big areas of value.
One is it automatically discovers data.
It allows you to intelligently curate, secure, and manage data
without data movement, and it also
allows you to apply governance and policy centrally.
Now, the technology under it is really
enabling you to manage distributed data,
and we're focused on three areas.
One is intelligent AI data-driven data management,
centralized security and governance,
and an integrated analytics experience
that combines the best of GCP data and open source tools.
At the event, Kumar Menon, he's the SVP
of Data Fabric for Equifax--
that's a great title by the way--
and he's taking us through how he's viewing
the use of this service.
This is a session I think you're really
going to love because it really shows where this industry is
going and where solutions like Dataplex, intelligent data
fabric solutions, will help your company manage this
distributed, highly sophisticated data you've
got across your organization.
STEPHANIE WONG: Yeah, and that's great.
That's for the intelligent data fabric.
So what about Datastream?
What does that new service do?
BRUNO AZIZA: So Datastream is also another one
I'm really excited about.
Datastream is a new serverless, easy-to-use change data capture
and replication service.
So let me run a few use cases by you
and see if they sound familiar.
Say that you have dashboards.
They're set up for users to make business decisions.
And data flows into your analytics database
to enable these dashboards, and it flows into some interval.
They may be every day, maybe every few hours.
And one day a data schema changes,
and you find out that something breaks.
The data is missing.
Sometimes you find out from someone in your organization
that's complaining saying, hey, the data doesn't make sense.
Does that sound familiar to you?
STEPHANIE WONG: Yes, unfortunately.
BRUNO AZIZA: So now, let's take another example.
Say you want to modernize your monolithic architecture,
and you want to go all-in into microservices-based,
event-driven architecture, and the model of the future.
You want to containerize.
You want to use Kubernetes.
But without a constant low-latency flow
of your organizational data into those services,
you're not going to be able to do it
because it's hard to break down the silos and isolated
databases.
It's hard to replicate data from one database to the other.
And it's hard to keep it in sync without a low
latency and highly reliable service, especially
when the databases are running different engines.
And so the answer to that, all these scenarios
I just talked about, is CDC--
change data capture-- and that's exactly what Datastream does.
Datastream allows you to deliver change data streams
from your Oracle and MySQL databases
into the Google Cloud Service like BigQuery, and Cloud
SQL, and Google Cloud Storage, and Spanner.
It also allows you to replicate with minimal latency, scaling
up and down with the serverless architecture,
and it integrates with your overall data ecosystem,
including data flow.
For instance, it integrates with data flow templates,
so you can pull change stream data
and create an up-to-date replicated table in BigQuery
for analytics for example.
And then finally, it allows you to replicate and synchronize
databases into Cloud SQL or Spanner for database migration,
and also hybrid Cloud configuration.
So a lot of capability here that's
going to allow you to keep all your systems in sync
for better analytics.
STEPHANIE WONG: Nice, so it's real-time, all the time.
BRUNO AZIZA: That's right.
All right, now, we've talked about intelligent data fabric,
real-time change data capture.
Let's talk about some analytics sharing, shall we?
STEPHANIE WONG: Yes, let's go ahead and do that.
BRUNO AZIZA: So we know that sharing analytics work
at scale, in real time, and securely is
challenging for organizations.
Traditional data sharing offers in the market today
often require batch data pipelines that
extract data from databases.
They store it into a FAT file, and then they're
going to transmit it again to be ingested in another database.
And this often results in multiple copies
of the same data which brings unnecessary cost,
and it can bypass data governance processes.
So we know today, 92% of executives,
according to the Boston Consulting Group,
wish that their company could increase
the use of external data, but there isn't a great market
solution to solve that problem, and this is really hard.
And so that's why we're introducing Google Cloud
Analytics Hub.
Now, I should say that we have a ton of experience
in this field, and folks listening to us today, in fact,
have contributed to building that experience.
BigQuery, for instance, has had cross-organizational in-place
and data sharing capabilities since inception in 2011.
And if we look at recent metrics,
they show us that over a period of seven days,
over 3,000 different organizations
were sharing more than 200 petabytes of data,
and these numbers don't include data
sharing between departments and within the same organization.
So we know a lot about data sharing,
and Analytics Hub is a lot more than just a data
exchange platform.
It's an analytics exchange platform.
So it's a new service that you can use to publish, discover,
and subscribe to share assets.
And it allows publishers to create exchanges
that combine public data sets with commercial data sets
and your own data sets.
Your publishers now are able to curate these exchanges
internally.
They can also do that externally.
And they can view aggregated usage metrics,
so they can see how popular their exchanges are.
Now, you're noticing I'm not calling this a data exchange.
Our vision here is much bigger than just data.
We want people to be able to share insights
that they build on top of BigQuery
leveraging the power of our platform.
For instance, BigQuery Machine Learning
is our machine learning that is built-in inside BigQuery,
and it's used by a large proportion of customers.
And so we believe with this new capability,
more opportunities for more organizations
will be created to share more than just data.
We're talking here machine learning
model, rich dynamic dashboards, et cetera.
STEPHANIE WONG: Wow, so that's incredible.
Now, Bruno, you started by talking about the value
of Google's open approach.
Analytics Hub is one example.
What about our work across multiple clouds?
BRUNO AZIZA: That's right.
There's a lot of announcements here
that are related to what's at the core of what we believe,
a world that is open.
And we want to provide the technology to meet customers
where they are.
So this week, for instance, we're
introducing two new game-changing innovations,
Google Looker on Microsoft Azure,
and BigQuery Omni for Microsoft Azure.
Now, Google Looker hosted on Microsoft Azure
is really a continuation of our commitment
to make sure that we can provide you
with the best, most modern, most open
enterprise business intelligence platform
regardless of your cloud choice.
So Google Looker, of course, runs on Google Cloud today,
and it's been available on AWS, but you can now
run it on Microsoft Azure.
So if all your data is on Microsoft Azure,
or if you're a Looker customer, and you want to also run
an instance on Microsoft Azure, this solution
is a great way for you to take advantage
of modern API-driven framework.
And most importantly, I think the powerful platform
that really Looker uniquely provides you with the ability
to build data-rich and beautiful experiences for your customers.
So that's for Google Looker.
BigQuery Omni for Microsoft Azure
now builds on the tremendous momentum
of our first cross-cloud analytics
solution we released last year, which is BigQuery Omni for AWS.
Now, for the first time, now our customers
are going to be able to perform cross-cloud analytics
from a single pane of glass across Google, Amazon,
and Microsoft Azure.
So this innovation really is at the heart
of what we believe multi-cloud strategy should be.
It makes it easy for customers to analyze data
wherever it's stored.
And in our session at the Summit,
we have Electronic Arts that talks about
how they're building a multi-cloud marketing
attribution model, and how they're
able to break server information silos without having
to move multiple copies of the data across the clouds.
We really expect that this offer is
going to be very, very popular with traditional enterprise
on Microsoft Azure.
STEPHANIE WONG: OK, wow, so, Bruno, we
covered a lot today here.
And, as you said, we just scratched the surface
with a few announcements out of the 13 or 15
your team's making this week.
So, of course, how can people get started?
BRUNO AZIZA: Thanks, Stephanie, yes, there
is a lot coming at you, and there's really three ways
we can get started here.
The first one is if you can attend the Data
Summit live, well, simply, go to the link down below here
and register.
It's free, and you'll get the opportunity
to interact directly with all presenters.
This event is for you, so don't be shy.
Ask your questions.
Interact with the community.
We want to make sure we get to the heart of your questions.
Second, if you can't attend the event live,
register anyway because you'll get access
to the replays and the resources after the event, which you'll
be able to view, and, of course, share with your colleagues
and your friends at work.
And then finally, if there's anything
that I can do to help you, just ping me on LinkedIn--
I'm going to put my LinkedIn profile down here--
and let me know how we did, and what more we
can do to help you.
STEPHANIE WONG: Wow, Bruno, so you've been very busy,
but this is all very exciting for the analytics world.
Thanks so much.
BRUNO AZIZA: Thanks, Stephanie.