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NEW QUESTION # 50
What is the default classification for a newly discovered application in the App Inventory in the Third-Party App Governance Admin Portal?
Answer: D
Explanation:
In Zscaler 3rd-Party App Governance documentation, the App Inventory is where administrators view and manage all discovered third-party apps, add-ons, and extensions. The "Classifying Apps" help article defines the available states: Unclassified, Sanctioned, Reviewing, and Unsanctioned. Crucially, it notes that Unclassified is the default state for any new application before an administrator evaluates it.
"Sanctioned" is used once the organization has explicitly approved an app for use; "Unsanctioned" is used when an app is not allowed; and "Reviewing" indicates it is under investigation. Those labels are the result of governance decisions applied after discovery.
ZDTE study materials on SaaS and app governance mirror this behavior: newly discovered apps enter the inventory without an explicit decision, allowing security teams to triage risk, review permissions, and only then mark them as sanctioned or unsanctioned. Because the default state for a new entry is explicitly documented as Unclassified, the correct answer is D. Unclassified.
NEW QUESTION # 51
Which type of sensitive information can be protected using OCR (Optical Character Recognition) technology?
Answer: C
Explanation:
Zscaler's Data Protection platform integrates Optical Character Recognition (OCR) into its inline Data Loss Prevention (DLP) capabilities. OCR enables Zscaler to extract text embedded within images-such as screenshots, scanned documents, or photos of forms-and subject that text to the same DLP inspection engines that normally analyze plain text content.
Once OCR has converted image content into text, Zscaler can apply predefined dictionaries, custom dictionaries, and advanced classifiers to detect sensitive data types, including personally identifiable information (PII) such as national ID numbers, passport numbers, addresses, or other regulated personal data. This is crucial because many data leaks occur via screenshots or scanned documents that traditional, text- only DLP engines would miss.
While OCR could, in theory, detect patterns related to network configurations, software licenses, or financial transactions, Zscaler's training and exam materials emphasize its use to protect sensitive data in images- especially user-related regulated data such as PII and other compliance-relevant information. Network configurations and software licenses are better addressed through configuration management and IP protection policies, and "financial transactions" describes activities rather than a specific information pattern.
Therefore, Personally Identifiable Information (PII) is the best and most exam-accurate answer for the type of sensitive information protected using OCR.
NEW QUESTION # 52
An organization wants to upload internal PII (personally identifiable information) into the Zscaler cloud for blocking without fear of compromise. Which of the following technologies can be used to help with this?
Answer: A
Explanation:
Zscaler's advanced data protection stack includes Exact Data Match (EDM), Indexed Document Match (IDM), dictionaries, and predefined DLP engines. Zscaler describes EDM as a technique that "fingerprints" sensitive values-such as PII from structured data sources (databases or spreadsheets)-so the platform can detect and block exact matches to those values while greatly reducing false positives.
With EDM, an on-premises index tool hashes the sensitive fields (for example, names, IDs, or other PII) and then uploads only these hashes-not the readable PII itself-into the Zscaler cloud. Zscaler documentation emphasizes that only hashed fingerprints are sent, allowing organizations to protect internal data "without having to transfer that data to the cloud" in plain form. This directly addresses the requirement to block exfiltration of internal PII without fear of compromise.
Dictionaries and core DLP engines focus on pattern- or keyword-based detection (such as generic PII patterns) rather than matching exact records from an internal dataset. IDM, on the other hand, fingerprints whole documents or forms (for example, templates or high-value documents) rather than row-level PII records. Therefore, for uploading organization-specific PII in a privacy-preserving, hashed form to enable precise blocking, EDM is the correct technology.
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NEW QUESTION # 53
The ZDX Dashboard is a comprehensive tool designed to provide a performance overview of an organization's digital experience. It encompasses various aspects to monitor and analyze performance, ensuring a smooth digital experience across the organization.
Which of the following is responsible for the automated root cause analysis within ZDX?
Answer: D
Explanation:
In the Zscaler Digital Experience (ZDX) section of the Digital Transformation Engineer material, Y-Engine is explicitly defined as ZDX's Automated Root Cause Analysis component. The EDU-200 and study-guide content describe Y-Engine as using machine learning to automatically isolate root causes of performance issues, correlating metrics across applications, networks, and devices so that IT teams spend less time troubleshooting and can get users back to work faster.
Several ZDX overviews and integration documents reiterate that Y-Engine is ZDX's AI/ML-based approach to detect what is causing the ZDX score for a given application or user segment to drop, effectively automating the "why is it slow?" analysis that would otherwise require multiple domain-specific tools.
"Copilot" in the Zscaler context refers to generative-AI assistance that can surface insights and answer questions, but it is built on top of underlying telemetry and correlation engines like Y-Engine; it is not the core Auto-RCA engine itself. "Application Performance" is a metric category within ZDX, and "OAuth request" is simply an authentication mechanism, not a diagnostic engine. Accordingly, the training content makes it clear that Y-Engine is responsible for automated root cause analysis, so option C is correct.
NEW QUESTION # 54
Which tunnel mode supports both web and non-web applications, ensuring comprehensive security for modern enterprises?
Answer: B
Explanation:
Zscaler Client Connector supports multiple tunnel modes to send user traffic to the Zscaler security cloud. In the Digital Transformation Engineer material, Z-Tunnel 2.0 is described as the recommended and most capable mode because it supports both web and non-web applications across all ports and protocols. This enables comprehensive inspection and Zero Trust policy enforcement for SaaS, web, and private applications from a single, unified tunnel.
Z-Tunnel 1.0 was primarily designed for web traffic, with limitations around non-web protocols and certain advanced use cases. As enterprises adopt more modern and diverse application stacks (VoIP, collaboration tools, custom TCP/UDP apps), Z-Tunnel 1.0 often cannot provide full coverage. GRE and IPSec tunnels (options A and C) are typically used for site-to-cloud connectivity from branch or data center routers, not as endpoint-based tunnels from user devices.
Z-Tunnel 2.0 uses an advanced encapsulation mechanism that can simultaneously support ZIA and ZPA, apply granular user- and device-based policies, and provide rich telemetry for analytics. It is explicitly positioned in Zscaler's training as the tunnel mode that delivers end-to-end protection for both web and non- web traffic, making it the correct answer for enterprises needing broad, modern coverage.
NEW QUESTION # 55
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