DEBI CABRERA: Do you need to monitor and protect
large amounts of sensitive data, but aren't always
sure where that data is or how it's
being processed and managed?
Today we'll talk about Automatic DLP, a service
from Google Cloud that is built to minimize
the risk of sensitive data being mishandled or exposed
and help you prevent privacy, security,
and compliance issues.
Before we continue, if you need a refresher on what data loss
prevention is, check out the link
in the description for our Getting Started with Data Loss
Prevention playlist.
First, let's understand how DLP Inspection works.
The Cloud DLP Engine inspects structured and unstructured
data and classifies it using what we call info types,
our predefined data tags.
Out of the box, DLP provides over 150 different info types,
including personally identifiable information,
financial data types, global and region-specific types,
and more.
And you can extend these with custom info types and detection
rules to meet your business's needs.
For example, the DLP Engine can tell you
where it found an instance of a credit card number,
even giving you details down to the byte
offset where it was found.
For BigQuery, an inspection job can
be configured to scan an individual table in a data set.
This will leverage the DLP Engine
to perform a deep scan of that table
to look for sensitive data elements.
Info type classification can be used
to make informed decisions about how you protect, share,
and use your data.
The DLP Engine and inspection jobs
are great at deep scanning data to get
very detailed information.
But when it comes to gaining visibility
across your entire organization, across thousands of projects
filled with data sets and tables,
this scale can become unmanageable pretty quickly.
And writing up some custom code to scan every table
can lead to a lot of overhead to manage.
So we made DLP automatic and developed a fully-managed data
profiling service that takes away that overhead and pain.
It gives you the same detection quality as DLP
and lets you protect data by identifying
where sensitive and high-risk data resides automatically.
It generates a set of metrics and insights or a data profile
from scanning the data.
Among these metrics are the protected info types
found in BigQuery tables, free text score, and data risk
level.
So you gain crucial insights into what kind of at-risk data
you are currently storing, allowing
you to take the appropriate steps to protect it.
Automatic DLP profiler scans are set up
with a simple configuration.
And we'll scan all BigQuery data sets and tables
in an entire organization, folder, or project.
You may be thinking, these wide scanning capabilities sound
great.
But what if I want to keep that detailed view of my data?
Well, you're in luck because this automatic service
was built to fit perfectly with the previous DLP
functionality, those inspection jobs we talked about earlier.
So you can get a view a mile wide,
and when needed, a mile deep when using these together.
And the fact that automatic DLP is fully managed
allows Google Cloud to take on the overhead
and allows you to focus on the outcomes and your business.
But wait, there's more.
Continuous monitoring automatically
profiles any new tables you create across your org
and periodically re-profiles the tables you modify.
Data profiles are generated in the same geographical region
that your data lives in, making sure to maintain
your data residency.
And deep technical knowledge of coding or embedding
isn't necessary to use the service.
You focus on configuring it to your needs,
turning it on with one click, and consuming the results.
And you get all of this with low overhead, which
means you don't need to manage or orchestrate your own jobs.
So scanning across your org is a breeze.
As a quick example, let's say you
have 150,000 tables across multiple projects
that you need to scan for sensitive data,
like Social Security numbers and email addresses.
When you turn on automatic DLP, you'll
see detailed metrics about each table and column
in your organization so that you can assess your overall data
risk and gain insights on where you have that sensitive data.
Executives who worry about maintaining security and data
compliance can see at a high level where risks may lie.
And data admins who are responsible for that data
can ensure all data is properly permissioned
or consider they're identifying the data
to protect it and improve compliance.
All that were just a few configuration
steps and the click of a button to turn it on--
easy peasy.
So let's recap.
Automatic DLP will help find sensitive data, including
unexpected places, keep up with data growth that
makes it difficult to manually inspect data,
and provide rich insights about data and data risk,
allowing you to manage data risk,
make more informed decisions, focus on the outcome,
and ultimately, help to safely accelerate your business
while we take care of the rest.
Thanks for watching.