Introduction
Workshop Overview
Dataparity Inc. is a mid-size financial services firm that has grown its SaaS footprint faster than its data governance. Sensitive payroll data is scattered across cloud storage, endpoints, and AI tools — and no one knows where it's going. Over four hours, you'll step into the roles of three Dataparity employees: Alex maps the risk landscape and builds enforcement policies, Kevin triggers every violation you configure, and Priya investigates and automates the response. One payroll file threads all three modules together.
Learning Path
Module Overview
Meet the Team
Dataparity's lead security admin. In Module 1, Alex maps the full risk landscape. In Module 2, Alex builds and enforces every DLP policy from scratch.
Not malicious — just a busy employee reaching for the most convenient tool. Kevin triggers every policy violation you configure, across three different channels.
Dataparity's incident responder. Priya picks up Kevin's violations, triages them, coaches him, escalates to management, and automates future response.
One payroll file appears in 5 labs across all 3 modules. Discovered at rest in Lab 3, exposed to Copilot in Lab 4, blocked in transit in Labs 6 and 7, blocked in a browser prompt in Lab 8, and investigated by Priya in Lab 9. Same file. Five different risk contexts. One platform.
Lab Tenants
Pre-populated with realistic production-like data. Shows what a mature Zscaler deployment looks like after months of collection. No configuration allowed.
A clean environment with no active DLP policies. You build everything from scratch. The blank slate is intentional — building the policies yourself is the exercise.
Open with this question to the room: "Before we start — how many of you know exactly how many cloud applications your employees are using right now?" Wait for answers. Then: "By the end of Module 1, Dataparity's answer will be 911. How close do you think your number is?"
This sets up the Shadow IT discovery in Lab 1 and immediately connects the lab to their real environment.