A central hub which lets orgs discover, scan, and classify all customer data no matter where it lives
Customer problems & Project overview
Our Customers have many internal systems that house their customer data, sometimes it's personal data. If there is a data breach and this data is not adequately secured, the company might be held legally liable❗
Also many of these companies are required by law to provide this personal data to their customers upon request- which they cannot adequately do if they don't know where or what it is.
The outcome here is for companies to centralize all data across their systems, generate reports, and integrate them with other privacy workflows. In a nutshell, smarter data governance ✨
What did I learn?
We built an interface that handles 3 main problems:
A way to browse the folder structure of the database to see what's in it.
A way to see all the personal data our system could find in the database in one view
A way to train the machine learning model on how to find personal data specific to the company's needs.
Role
Product designer
Duration
3 months
Step 1 → Discovering data collected by your Company; usually stored in enterprise
database systems like Oracle, Salesforce, Redshift. These come in as Data silos
See connected data silos
Current actions running on the silos
All data silo states
You're first faced with the empty state, and the CTA prompts you
to manually add your Database. They show up in the Active tab 👇
These cards show all the possible states of a Data silo
In the configuration tab, Silo discovery can be turned on so Transcend periodically searches
for new silos. These become available in the inactive tab
Step 2 → Browse schema. Data silo browsing experience
✅ Case 1 - User is opening a completely scanned Data silo
✅ Case 2 - User is opening a Data silo still scanning
✅ Case 3 - The scanned Data silo is empty
See all the states the user can run into
Filtering the silos you see by 3 parameters
Browse silos filtering
Filter by:
Data silo type
Percentage classified
Owner
Step 3 → The training wizard
Now the scanning is complete, and all Datapoints are discovered, it's time to Train the machine learning model.
Transcend picks random columns, and wants you to confirm/deny the suggestions. How this works:
1) Looks for patterns in the silo, and displays that match a data category
2) Prompts you to confirm match or deny mismatch
Other states
✅ Case 1 - User attempts to Train a model while the Datapoints scan isn't complete
✅ Case 2 - User attempts to open a silo is discovered from Transcend's period scan
Step 4 - Datapoints
Final tab - Overview
This is the summary of the company data from all Data silos
How the solutions performed
Currently 2/3 of all Transcend customers use this brand new feature, which was introduced just last year.
© November 2024