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BRUNO AZIZA: Hi, everyone.
I'm Bruno Aziza, and welcome to another episode
of Data Journeys.
This is where we come to learn from leaders in data
their lessons, their do's and don'ts, and their journey.
Today, I have the pleasure of talking to Bala.
He's the Sr Director of Data Infrastructure
and Cloud Engineering at PayPal.
Bala, thank you so much for taking the time
to talk to us today.
BALA NATARAJAN: Thank you very much,Bruno.
The pleasure's mine.
BRUNO AZIZA: All right, well, let's get right into it.
Let's first talk about PayPal and some of the data-use cases
that you have.
BALA NATARAJAN: PayPal is a global leader
in online payment solutions with more than 350 million accounts.
We operate in 202 countries and 25 currencies around the world.
We enabled global e-commerce by making payments
possible across different locations, currencies,
and languages.
We are one of the largest FinTech players
in the e-commerce ecosystem.
Due to the unique position in the market,
data has always been central for both payment processing
and for our offline systems, Bruno.
BRUNO AZIZA: So we're talking here,
real-time decision making.
You're talking about serving finance, marketing, sales,
just about everyone in the organization.
How did PayPal and why did PayPal become so data hungry?
BALA NATARAJAN: That's a great question, Bruno.
Given that PayPal's size and the market
that we are serving in, some of our product analysts,
financial analysts, risk processing,
complaints processing all of them
require data, fast and secure access to data
to make their decisions.
Some of them are real-time, some of them are offline.
Due to this, our data volumes have grown 400%
over the past two or three years.
Our resource demands to process this data for critical business
functions, have increased 300% over the past just two years.
And we spent 25% of the resources just moving data
across various end systems, and also validate the data
before we give it to an end user.
So this has been a huge drain of resources across the ecosystem.
This is when we started looking at Cloud
to see where we could optimize some of these inefficiencies.
BRUNO AZIZA: So that's great because now you're
using BigQuery, Dataproc, Bigtable, Cloud
SQL, Pub/Sub, Cloud Functions, but previously, you
were on-premise.
And so with the increase of data volume
and the increase in customers and number of transactions,
tell us a little bit about how you
handled that migration, which you executed on fairly quickly.
BALA NATARAJAN: I have to talk about a recent project
that my team was involved in.
As I speak today, one of the teradata
clusters my team, some of our community was using,
has been completely dismantled now.
This cluster, as a history, was predominantly
used by product and financial analytics folks.
This set of users were the ones who are providing predictions,
looking at the data, how our products stood, and predicted
what the revenues would be for PayPal.
Interestingly, our COO would be getting guidance based
on business team's foot work.
As I speak today, this cluster not only has been dismantled,
and it just took one year for us,
from part to part to complete this work.
Last year, when COVID hit, the data volumes
grew for us because there's a lot more payments than normal
when the pandemic hit everyone.
Now, this community was trying to figure out
how our products were doing.
They were also trying to provide guidance
in terms of our revenues, as well as our product portfolio.
We realized that this cluster was not
ready to handle huge workloads.
At the same time, it was also not serving
the business demands that these analysts were
requiring it to do.
So it was in June, 2020, we decided that we
had to move to the Cloud.
And it was after the Independence Day of 2020
when we decided that we'd set up a network
to try some data in the Cloud.
So in the past one year.
I'm very proud to say, my team migrated,
not just simply migrated, we started
the evaluation process, set up the networks, secured the data,
did two rounds of penetration testing, copied close to 30
plus petabytes of data.
We converted thousands of workloads.
We converted close to give or take
800 dashboards from Tableau.
Streamlined the lifecycle of analysts, who
are approximately 800 users.
And we also dismantled the cluster.
So all of this took just one year end-to-end.
So I'm super proud of what my team has done in the past one
year.
BRUNO AZIZA: That's amazing.
If you look at how other companies migrate,
it typically takes more than this much time,
especially as you're expanse in growth,
you have hundreds of users, and you also
change the way you think about the data.
Can you tell us a little bit about how
you handle BigQuery streaming?
And how that's part of your architecture, as well?
BALA NATARAJAN: So as I said, as we did this change,
we also offered Looker and we also
found out some of the pipelines that
was trying to get behavioral data from the site was very,
very slow and our analysts did not like it.
So the team that was moving behavioral data,
started using BigQuery streaming to move this data quickly
into BigQuery.
And is now, we offer that data back to our customers
in less than five minutes, which was a huge change from eight
hours that it takes for them to look at data today.
So this is what we have been able to leverage and use
the Cloud for.
And this has made our analyst community
super happy in terms of what they see, what they're offered,
and also the business agility that they're able to provide
back to business.
BRUNO AZIZA: So from eight hours to five minutes, that's really
quite exceptional, the agility you're
going to gain with just making this change.
I can't wait to hear about your best practices and the worst
practices.
In fact, let's get started with that.
Let's talk about maybe, the positive first.
What would you say is the number one best practice
everyone needs to consider when they're
migrating to the Cloud such amazing workloads, like yours?
BALA NATARAJAN: PayPal has always prided in security,
and that's number one in every exec's mind at PayPal.
We believe in earning the trust of our customers,
and we never want to let our customers down.
So securing our data using strong authentication
authorization is very, very fundamental to what we did.
And that's very, very important.
And that's the first thing we designed into the system
as we decided to move to BigQuery.
BRUNO AZIZA: So you talked about security as first principle.
What does this mean, did you have to hire new people,
did you have to employ different practices?
BALA NATARAJAN: The interesting part of our journey, so far,
Bruno, has been that we didn't have to hire new people.
We were able to train a lot of our existing teams.
They were told about the importance
of securing the data.
They were taught about risk management of data.
And that helped us gain a lot of credibility with our community
as well as our users.
We put first principles.
We did discuss quite a bit in terms of how to secure data.
So we did adopt new practices and patterns to secure the data
and offer the data back to customers.
BRUNO AZIZA: So that's great, which is build security
from day one into your process.
What about the flip of this?
What is it that you would advise people
need to avoid as they're migrating,
things maybe they might not think about today?
BALA NATARAJAN: We learn a lot during this large migration
projects.
We learn in terms of what to do, what not to do.
But sometimes I find that things tend
to take their existing patterns and principles that they're
comfortable with to the Cloud.
For example, they tried to mirror their data pipelines
and the experience they provide to their customers
to the Cloud, the same way that they did on-prem.
So it can be nice to think through that before you
replicate the experience.
That sometimes becomes too kludgy, too hard,
and it is probably not in the best
interests of your business.
That is something I would avoid if I
do this project all over again.
BRUNO AZIZA: So try not to mirror the existing pipelines.
Essentially, nobody wants to waste the opportunity
of a good transformation.
And so use that as the opportunity
to, essentially, modernize your processes as well, I'm
assuming.
BALA NATARAJAN: Exactly.
BRUNO AZIZA: Well, Bala, thank you so much
for your time today.
I could talk to you for hours.
And this was really interesting and educational for us.
We learned about security as a first principle.
We learned about not wasting the opportunity
of a good transformation, both the physical stuff
but also the processes and the way
we do implement various pipelines.
I want to thank you for your time today, Bala.
BALA NATARAJAN: Thank you very much, Bruno.
It's a pleasure is mine.
BRUNO AZIZA: And I hope that people
are going to reach out to you.
You wrote a great blog that documents,
not just the process of migration,
but also the benefits that you got from moving
from on-prem to the Cloud.
I hope they'll reach out to you.
Until next time, I'm Bruno Aziza.
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