Understanding Lightbeam: Labeling Data Repositories for Smarter Governance
Lightbeam automates labeling of data repositories—classify documents by policy, protect sensitive data, and simplify governance.
Understanding Lightbeam: Labeling Data Repositories for Smarter Governance
In today’s data-driven world, managing massive volumes of documents begins on day one of an employee’s journey.
In this Understanding Lightbeam video, see how automated labeling improves governance:
Identify documents across repositories and know who has access
Apply policy-based classification without altering original files
Strengthen governance and compliance with consistent labeling
Lightbeam helps you protect sensitive data and enforce governance policies automatically.
Transcript
Recently I came across statistics that said that
for a mid-size
or an enterprise company,
a new employee joining such companies has access
to 5 million documents on day one of joining.
Just think about that for a second.
That has huge data security implications.
As an organization, what you might want to do is
to understand what type of documents do you have,
who has access to those documents
and with whom Have these documents been shared perhaps
internally or externally of your organization?
The first step in doing that level of data governance is to
label your entire document state
and infrastructure according
to your policies and principles.
As an example, let's say you have a policy that says
that any document that contains a patient name,
presumably you are a healthcare organization,
should be labeled as sensitive.
If a document contains a patient name
and address, perhaps it should be labeled as restricted,
and if a document contains patient name, address,
and a credit card or a social security number,
then it should level confidential.
Now these are simple policies that you can specify.
You can also specify more complex policies within lightbeam.
What Lightroom does is it looks at these policies
that you have then as it goes and scans millions
and millions of your documents,
and if it detects a document, it contains a name, an SSN,
an address and a credit card.
It'll automatically label that document as confidential.
Note that the labeling does not alter the
content of this document.
The document stays as if it is just enriching the metadata
of this document.
for a mid-size
or an enterprise company,
a new employee joining such companies has access
to 5 million documents on day one of joining.
Just think about that for a second.
That has huge data security implications.
As an organization, what you might want to do is
to understand what type of documents do you have,
who has access to those documents
and with whom Have these documents been shared perhaps
internally or externally of your organization?
The first step in doing that level of data governance is to
label your entire document state
and infrastructure according
to your policies and principles.
As an example, let's say you have a policy that says
that any document that contains a patient name,
presumably you are a healthcare organization,
should be labeled as sensitive.
If a document contains a patient name
and address, perhaps it should be labeled as restricted,
and if a document contains patient name, address,
and a credit card or a social security number,
then it should level confidential.
Now these are simple policies that you can specify.
You can also specify more complex policies within lightbeam.
What Lightroom does is it looks at these policies
that you have then as it goes and scans millions
and millions of your documents,
and if it detects a document, it contains a name, an SSN,
an address and a credit card.
It'll automatically label that document as confidential.
Note that the labeling does not alter the
content of this document.
The document stays as if it is just enriching the metadata
of this document.
