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DEBANJAN SAHA: Hi, everyone.
I'm Debanjan Saha, VP of engineering
and GM of data analytics at Google Cloud.
Thank you for joining us today at Next OnAir.
This week we are going to focus on data analytics.
I'm going to kick it off with an overview of our portfolio,
highlighting some of the new product launches.
I'll also talk about our strategic priorities,
and what's next for data analytics at Google Cloud.
Throughout the week, you're going
to hear from my teammates about our roadmaps
and under-the-hood technical details about our products.
We'll also have our customers and partners
telling their stories about their data journey
with Google Cloud.
So let's get going.
Big data is in our DNA.
In fact, it is part of our mission statement
to manage and organize the world's information.
There are many Google products that
handle massive amounts of data.
Over the past 20 years, to support these products
and their users, we have built a powerful data analytics
platform.
This platform is now available to all our cloud customers.
Our data analytics platform offers a comprehensive set
of analytics services, everything
from data collections to processing, analysis,
and activation.
In the last year, we have added a number of new services--
Cloud Composer, our workflow engine, Cloud Data Fusion,
a visual ETL system, Cloud Catalog,
our metadata management service.
I am also really excited to have Looker join our family.
Our existing products, like BigQuery, Dataflow,
and Dataproc added exciting new features.
Now, good tools are only one part of the story.
Without data, analytics is not very meaningful.
And that's why we spend a lot of time making sure data
is readily available to our customers.
This includes various Google data sources--
Google Analytics, search trend, maps, and mobility data--
data from various operational databases in Google Cloud--
Cloud SQL, Bigtable, Firebase, et cetera--
data from external sources, as, for example, SaaS
and third-party applications like Salesforce, Adobe,
and SAP.
Ready availability of valuable data
is a big reason why customers come
to Google Cloud for their analytics needs.
Well, we have the tools, we have the data.
How do we translate that to drive business outcomes
and do that quickly?
That's where solutions come into the picture.
We are codifying common use cases
in various different industries into solution blueprints.
Customers can begin their journey with these blueprints
and build custom applications and solutions
in a matter of days, not months.
This accelerates time to insight and time to value.
For example, we have put together
this solution blueprint for Google Ads and marketing
platform activation using BigQuery and its built-in ML
functions, and Looker, using a variety of data sources
available in Google Cloud.
We have many more examples like this.
Here is a list of various solutions in various industry
segments that we are working on.
Solutions are a high priority for us
and a major area of investment.
Let me now talk about our strategy going forward.
Our vision is to build an enterprise-class analytics
platform, an analytics platform our customers can depend on
for their most demanding mission-critical workloads.
And we want our platform to be open, intelligent,
and flexible.
Let me walk you through this.
Why open?
Well, our customers don't want to be in walled gardens.
They want choice, both first-party
and partner services.
They want portability so that they
can move into cloud easily and migrate out if they want to.
They want support for hybrid and multicloud.
Speaking of multicloud, in a recent Gartner survey,
80% of public cloud users indicated
that they use multiple cloud providers
and will continue to do so.
As you know, we are a big proponent of multicloud,
and believe that multicloud is the future.
That's why I'm really excited to have Looker join our family.
It is truly a hybrid and multicloud business
intelligence platform that runs on Google, AWS, Azure,
and also on-premises.
Looker helps you create semantic models and data API
on all your data across clouds and on-prem.
You can use this to build interactive dashboards, custom
workflows, and applications.
I'm also really excited to introduce BigQuery Omni.
Many of you use and love BigQuery,
our flagship data warehouse.
You have asked if you can make it available on AWS and Azure.
Well, consider your wish granted.
BigQuery is now available on AWS for customer testing.
And it's coming to Azure soon.
With BigQuery Omni, we are breaking down the data silos.
No matter where the data is--
Google, AWS, Azure-- you'll be able to query
it using the same familiar BigQuery UI and standard SQL.
Powered by Anthos, it is the first fully managed multicloud
data warehouse from a major public cloud vendor.
Everyone wants to use intelligence services infused
with AI/ML.
We have some of the most advanced AI/ML technologies
in the world.
What is unique about our approach is that
AI/ML-augmented analytics-- is that we make it seamless.
That is, we've seamlessly integrated most sophisticated
AML technologies into our systems, tools,
and processes so that users don't have to learn anything
new to take advantage of them.
It is a huge plus for the adoption of AI/ML.
Let me give you an example.
Let's take a look at BigQuery ML.
It allows you to build custom ML models using standard SQL
with data already stored in BigQuery.
So data analysts can build sophisticated models
and use them for inferencing using simple SQL without having
to learn anything new.
How awesome is that?
We are taking it a step farther.
We are using these models to build solutions
that solve real business problems like recommendation
systems, customer segmentation, anomaly detection,
and forecasting.
One of the solutions we are launching this week
is anomaly detection.
It has use cases in different industries,
as, for example, flagging fraudulent stock transactions
or money transfer in financial industry,
detecting all traffic patterns between a pair of senders
and receivers in telcos.
Flexible-- we have a diverse customer base.
They are in different industries, have different use
cases, and different business models.
And they want choice.
And they want flexibility in how they use our product,
flexibility in pricing models.
We want to meet our customers where they are.
Let me elaborate with an example.
A lot of our customers use BigQuery.
Their use cases are different.
And so are their access and analysis patterns.
For example, data scientist wants
to access data stored in BigQuery directly
using the Storage API.
Data analyst likes the SQL interface.
Business analyst accesses BigQuery
through their favorite Bi tool, like Looker and Tableau.
We have now added a natural language interface to BigQuery.
This is the kind of flexibility our customers are looking for.
I'm really excited about Data QnA.
All business users, as, for example,
agents in call centers, traders in stock exchange,
will now be able to use the power of BigQuery.
It is true democratization of analytics.
We talked about a lot of cool things.
But those only matter if the platform is dependable.
That's why we are laser-focused on availability.
We just announced four 9's guaranteed SLA for BigQuery,
best in the industry.
Our platform offers scalability and security
that meet the requirements of the most demanding workloads
and compliance and governance control
required in the regulated industries like finance
and health care.
But the best testament to our proven dependability
is the adoption of our services by our customers.
The largest enterprises in every major industry segment
use our analytics services.
And it is not just the big enterprises.
Customers big and small and customers all over the world
are using our services in increasing numbers.
But instead of me talking about our customers,
let's hear from one of our very important customers.
I am pleased to introduce to you Vittorio Cretella,
CIO of Procter & Gamble.
Vittorio, first of all, thank you
very much for joining us to share a bit about your data
story.
Could you introduce yourself first, though?
VITTORIO CRETELLA: Sure.
And thanks for having me here at the Next OnAir, Debanjan.
My name is Vittorio Cretella.
I'm the CIO of Procter & Gamble.
And I've been working as an IT professional
in the CPG industry for many years.
My passion is to create consumer value with technology and data.
I must tell you, P&G is the best company
in the world to do that.
Our aspiration is to serve consumer
in the world better than our best competitors
in every category and every market where
we choose to compete, and in the process creating shareholders
value.
DEBANJAN SAHA: P&G is a 180-year-old company--
or should I say a 180-year-young company.
You clearly know a thing or two about consumer experiences
and have gone through a few transformations over the years.
So how are you thinking about data analytics in the cloud
to deliver even better experiences for your customers
and help transform P&G again?
VITTORIO CRETELLA: Yeah, Debanjan, our objective at P&G
is to understand consumers and serve them better
than anybody else.
And we do that by becoming a datacentric business.
Like many other businesses, we use
data for descriptive and diagnostic purposes
to understand what happens and why.
But where we excel is using data to make predictions
to understand what will happen next and understand
whether a promotion will be successful to decide product
assortment by clusters or stores to manage spikes in demand
across our supply chain like it happened during the pandemic.
And I can name many other examples.
Now, to achieve that, we can tap into a very rich data lake
environment.
And we benefit from the skills of our data scientists
and business analysts, who create algorithms to solve
some of the toughest questions.
Increasingly, we turn those predictions
into a prescription.
So we automate the result of this algorithm
and inject them into our transactional and planning
systems so that mainstream decisions are automated.
Now, the cloud provides us the agility to do that at scale
with three things.
Number one, the capacity to store
big amounts of data on demand.
Second, the tools and the machine learning
libraries to work on those data.
And last but not least, the means
to ensure operational reliability and the protection
of data privacy.
Now, getting there means we need to invest in our partnerships.
And Google Cloud, for one, helps us
deepen our technical capabilities
and supports our needs across the data stack.
DEBANJAN SAHA: Thank you for that.
Now, speaking of Cloud, and Google Cloud, specifically,
can you share a little bit more about how Google Cloud fits
in your data strategy?
VITTORIO CRETELLA: Sure.
Let me say first that we are on a multicloud data lake
environment, with several petabytes of data
across functional areas and with many business use cases.
Our partnership with Google Cloud started about a year ago,
with the objective of storing analyzing our brand
and marketing information.
And since then, we have been on a journey
to migrate all our consumer information in a data
lake which currently is larger than 4 petabytes.
The data lake provides one unified view of consumers
and allows to orchestrate effectively
omnichannel consumer journeys, which
means enabling to serve the right content
to the right audiences at the right time
on the right channels.
Now, we take advantage of many great products
in your analytics portfolio.
And I'd like to call out one in particular
that I've been really impressed by, which is BigQuery.
And since we started working with BigQuery,
the technology performs incredibly well.
We are using it both for data science purposes,
but also to serve descriptive and diagnostic information
to larger audiences thanks to the compatibility
task with our standard visualization tools
from other partners.
And that, I believe, is a great story.
It's a great story when we can make our tools work better
together so everyone can deliver against the business
and analytics objectives.
DEBANJAN SAHA: That is a great story indeed.
You touched on using other tools and technologies there,
Vittorio.
As you know, we are a big believer
of customer choice and open platform.
Can you share how that's influenced your decision
to work with Google Cloud?
VITTORIO CRETELLA: Yes, Google Cloud
is a strategic partner in our multicloud environment.
And one of the things that I've appreciated
is how your teams work together as an extension of our teams
to help us bring transformation initiatives to life
without pushing us into a closed ecosystem, a closed software
environment.
Now, our future is with a multicloud environment.
And we are really excited by what
working with Google Cloud will deliver,
will enable us to do and to achieve, to really
find the experiences for all consumers of Procter & Gamble
brands.
DEBANJAN SAHA: I'm intrigued by those future experiences.
Vittorio, is there anything else you'd
like to share with us today?
VITTORIO CRETELLA: Well, I believe
you will see more and more examples of connected products,
where our consumers opt in to share information and receive,
in exchange, personalized services and advice.
And I'm sure you're familiar with some of them, such as Lumi
by Pampers, the sleep routine system that helps parents
to track day-to-day developments and monitor their babies
24 by 7, or the Oral-B iO series toothbrush that
has a unique and very effective brush head design,
but also shows you how to effectively improve
your teeth cleaning routine.
All this is made possible by data,
including the information we safely store on Google Cloud.
And things will evolve.
And it'll be interesting to see how.
DEBANJAN SAHA: Indeed it will.
Thank you for joining us for Next OnAir, Vittorio.
It goes without saying we very much appreciate
your time and your partnership.
Thank you.
VITTORIO CRETELLA: Thank you, Debanjan.
It was a pleasure.
Have a safe and productive summer.
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DEBANJAN SAHA: Just to wrap up, throughout the week,
we are going to cover different aspects of data analytics
services in Google Cloud and how we
are building a platform that is open, intelligent,
and flexible.
Please tune in and participate in
the 40-plus breakout sessions from Googlers, our customers,
and partners.
Thank you.