Before getting started with Osano's data mapping tools, it’s helpful to think about a few key questions. Don't worry—these steps are straightforward and will allow you to think through the process of starting your data mapping journey in more manageable milestones!
What are you using as your data SOURCE?
First, decide how you will source your data:
A.) SSO (Single Sign-On)
Examples: Okta, OneLogin
B.) CDP (Customer Data Platform)
Examples: Segment, RudderStack
C.) Cloud DB Services
Examples: Amazon Aurora RDS
D.) Manual Entry via an Assessment
Example: ROPA (Record of Processing Activities)
E.) No Source, Manual Entry of Data Stores
You will enter each Data Store individually.
F.) A Combination of the Above
Mix and match methods as needed.
Identify WHO you need
Depending on your chosen data source(s), you'll need to involve the appropriate team members:
-
If you chose A (SSO):
You’ll need your SSO Administrator. They should have an Osano User account and will need their SSO admin credentials to connect Osano (in read-only mode) to your SSO provider.
-
If you chose B (CDP):
You’ll need your CDP Administrator. They will require an Osano User account and their CDP admin credentials to connect Osano (in read-only mode) to your CDP provider.
-
If you chose C (Cloud DB):
You’ll need your DB Administrator. They will require an Osano User account and their Cloud DB admin credentials to connect Osano (in read-only mode) to your DB provider.
-
If you chose C or D (Manual Entry):
You’ll need to involve all Data Owners within your organization, typically department heads who can audit their teams to identify tools or locations where company data is stored.
Which Applications should convert to DATA STORES?
Your Data Stores make up the main components of your Data Map.
When using methods A, B, or C from sources, you are automatically discovering systems that may contain PI. Appropriate systems should then be converted into Data Stores. Data Stores represent locations where Personal Information is stored or locations where PI may be found. Data Stores will also be used to populate your Data Map and default flows as well as assist with your Subject Rights response workflows.
How would you like to interact with your DATA STORES?
Choose how you would like to interact with your Data Stores:
A.) Automatically
B.) Manually
C.) A mix of manual and automated
Who You Need
If you chose A (Automatic):
You’ll need to assemble your Data Store Owners. These owners will require Osano User accounts and their application admin credentials to connect Osano to each automated Data Store. Admins must provide the necessary read and/or write access (depending on whether you’re utilizing automation for deletion).
If you chose B (Manual):
You’ll need all Data Owners within your organization. Setting up manual Data Stores may involve collaboration with team members like Engineers, HR, or Legal Counsel, who can highlight PI within these systems and suggest necessary data fields or assignees for compliance and accessibility.
If you chose C (Mixed):
You’ll need a combination of the above resources for both automated and manual setups.
Your Data Map
Once your Data Stores are configured, you can start building and refining your Data Map.
Your Data Map will automatically populate with the Data Stores and related vendor information you’ve entered. From the Data Map interface, you can establish relationships and flows between Data Stores, offering a clear visualization of your systems and data flows.
The Data Mapping Getting Started Packet
As you get started understanding Data Mapping, here are some useful resources to lead you to success!
Start with the Introduction to Data Mapping to gain a comprehensive understanding of the entire Data Mapping process from start to finish. Once you've familiarized yourself with the basics, delve deeper into the foundational elements of your data map by examining your sources. Learn how these sources identify and reveal discovered data and explore the intricacies of transforming that discovered data into functional data stores. Finally, explore the data map visualization to see how these components integrate to create a cohesive view, and identify opportunities to refine and optimize the visualization as needed.