ANITA KIBUNGUCHY: Finding your data assets is one thing.
Managing both your technical and business metadata while
maintaining proper security requirements
is a whole other beast.
Luckily, Data Catalog can help.
Stay tuned as we cover how to add schematized tags
to your data assets as well as show you
how integration with Cloud Identity and Access
Management or Cloud IAM provides ACL controls on your metadata.
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Data Catalog is a fully managed and scalable data discovery
and metadata management service that empowers organizations
to quickly discover, understand, and manage
all their data in Google Cloud.
I am Anita Kibunguchy.
And today, we'll be tackling how to understand your data
assets with schematized tags in a safe and secure way.
Just like sticky notes, Data Catalog tags
act as annotations.
Whereas other data catalogs capture tags a simple text
strings, Data Catalog captures business metadata
in a schematized format via tags.
These tags can be created through the UI as well
as custom APIs.
Users can now define a business tag as string, double, Boolean,
or enumerated-- enum--
making it easy to catalog and find data assets.
So you've heard us talk a lot about technical and business
metadata.
So what do we mean by these terms?
Technical metadata is data that's
already saved in GCP services, such as table names, column
descriptions, and date created.
This data is automatically ingested from the data source
into Data Catalog without any involvement on your part.
For example, if you add a new table to BigQuery,
it will show up in Data Catalog in a matter of seconds.
On the other hand, business metadata
are tags that provide additional business information that
is valuable to a customer.
This could include PII, delete-by dates,
business logic, data quality scores,
as well as governance tags.
By adding business metadata, data assets
become more searchable and usable for your team.
Let's take a look at how you can add
rich information to your data assets with tag templates.
On the Data Catalog home screen, scroll to Tag Template section
and click on Create a tag template.
Here, you can define the template ID,
display name, as well as add attributes
and define their type.
Each attribute type can be string, double, Boolean,
or enum.
Once you've added all your attributes,
click on Save Template.
Creating a tag template can also be done programmatically
using custom APIs.
Let's learn more about an existing tag template.
On the Data Catalog home screen, scroll to the Tag Template
section and click on Explore tag templates.
We'll look at the Data Governance tag templates.
This template has tags to help the data governance
team certify specific data assets for use.
It also lets approved users know which data assets they can use.
You'll notice that each attribute has a type as well.
For data classification, the type is enum.
From there, the data governance team
can now define whether the data asset is public, sensitive,
confidential, or regulatory, and can then
apply the applicable controls around it.
Now that you've explored a tag template, let's look
at how the integration with IAM helps with access
control of your data assets.
Instead of having to set separate permissions or ACLs
to register data assets, Data Catalog
auto-ingests tactical metadata and honors existing source
ACLs.
This means that if a user already has read access
to all data assets in BigQuery, then
they'll be able to discover and have read access to those data
assets in Data Catalog.
Similarly, this IAM integration allows further access controls
to be set.
With Data Catalog, you can set read access,
metadata read-only access, and no read or no metadata read
access.
Depending on these permission settings,
users' search results and access can
be controlled, keeping highly sensitive data limited to those
with the necessary access.
Thanks for watching, and please check out all our Data Catalog
videos and visit our website to learn more.
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