How to Automate Data Subject Requests (DSRs) with Lightbeam | DSR Compliance Made Easy

Hello, my name is Tyler
and I'm a solutions engineer here at lightbeam ai.
I'm here to quickly talk about data Subject requests
or D-S-R-A-D-S-R is a formal request made by an individual
to an organization
to exercise their rights over their personal data, uh,
that is granted to them by laws such as the eus GDPR.
And I will quickly demo this for you here in a moment.
Light beam's, incredible capabilities
to provide data subject requests
within the lightbeam platform.
So first I need to explain a little bit about
how Lightbeam can provide the contents necessary to
basically proctor those data subject requests.
So the first thing that we do is we actually scan the entire
data repository, whether it be structured data,
unstructured data on premises, uh, is environments
and or SaaS environments to get a complete lay of the land,
to find all the different areas for where into
what we call entity resolution data resides.
Within this. This would include the ability
to find PII wherever it sits,
and to provide unparalleled correlation for
that user information across all
of the different data repositories.
So in this particular instance,
I'm showing Lance Margaret Estrada.
Lance's data resides not only in
G Drive, but also Gmail, JIRA, Azure, blob, Postgres,
and other data sources.
And we found Lance's information as names,
email addresses, social security numbers, et cetera.
It doesn't matter where and
or how this data resides, we're going to find bits
and pieces of this and automatically provide
that correlation for Lance.
And so that when it comes time
to processing Lance's specific data, we will be able
to show you exactly where that data sits for Lance.
So a little bit about the data subject request now
and actually how wiping Pro
processes all of that information.
First off, we have the various
workflows already defined within the platform, whether it be
for the actual messaging templates
for the requests being created and
or, uh, reclosed rejected, et cetera.
Then we provide the specific workflows necessary, including
the approvals, the data discovery validations,
all the way down to the report generation enclosure.
From here, we assume now that we have everything built out,
including the form to process all
of the different information, right?
So you have the ability to generate everything
that you need, uh, within this platform, such as here's
how you would adjust this information for a user to
input their name, validate the, their current request
for the platform, and even include things such as, uh,
capcha in terms and conditions.
Once everything is all set up, it's super easy
to actually receive that data.
So we actually begin to receive Lance's information.
We can see specific information associated with it.
This is the email address that was sent.
Uh, we've already validated his particular email.
We've recorded the request details.
And next, this is where it gets really fun, if you will,
if you or for a person who actually has
to process in this information.
Here is where we actually provide
true correlation showing you wherever we found
Lance's data existing.
So within this, we provide that specific workflow as, uh,
say particular tickets where you can actually work
through the process to say, yes, indeed.
We know exactly where Lance's data is.
This is a data, uh, attribute request to be deleted,
and we provide all of this information for the,
essentially the data process owner to go through
and, uh, remove this data, right?
We also give the, uh, process owner the ability
to do things such as reject tickets
or reassign tickets as necessary so
that when everything is completed, we give you the ability
to actually have those reports automatically made
and be sent back to the original requester.
I hope this proves as a quick
and easy example of how Lightbeam can really save you a lot
of time and, uh, really provide a lot of
that clarity you would need
for providing a data subject request.