Intune Advanced Analytics vs DEX Platforms: Why Telemetry Depth Still Matters
A practical guide to deciding when Microsoft Intune is enough—and when deeper digital employee experience telemetry becomes essential.
The question many clients are now asking
Many clients are reviewing their digital employee experience strategy as Microsoft continues to strengthen analytics within Intune. With core Intune capabilities commonly available through Microsoft 365 E3 and Advanced Analytics now available through Microsoft 365 E5, the natural question is whether they already have everything they need.
For organisations already invested in Microsoft 365, the case can appear compelling. Intune brings endpoint management, compliance, security, inventory, device-health insight and troubleshooting into a familiar platform. Advanced Analytics adds richer performance reporting, battery insights, anomaly detection, device timelines and near-real-time Device Query capabilities.
This is prompting clients to reassess new or existing DEX investments and ask a more fundamental question: does Intune now provide enough visibility and operational insight on its own, or is there still a business case for a dedicated DEX platform?
The answer is not found in a feature checklist or licensing bundle. It depends on the outcomes the organisation expects to achieve. Intune is primarily a management, security and fleet-analytics platform. A DEX platform is designed to monitor and improve the employee’s live experience across endpoints, applications, networks, collaboration services and virtual sessions.
A device can be compliant, encrypted, patched and correctly configured and still deliver a poor employee experience. This article explores where Intune may now be sufficient, where a DEX platform still adds value, and how clients can make that decision against measurable operational and business outcomes.
- Start with the business outcome, not the product comparison
The technology discussion often begins with a feature checklist. A more useful starting point is the business outcome the organisation is trying to achieve.
Executives may be concerned with:
• The productivity cost of slow or unreliable technology
• Service desk demand and operational cost
• Employee satisfaction and digital friction
• The effect of poor collaboration quality on customers
• Hardware lifecycle and procurement decisions
• The ability of IT to prevent incidents rather than react to them
Technical and operational teams may be asking:
• Which devices are experiencing CPU, memory, battery, or application problems?
• Did a configuration change introduce instability?
• Can the service desk diagnose an issue without taking control of the device?
• Can a transient problem be identified while it is happening?
• Can the platform correlate device, network, application, and session telemetry?
• Can known problems be resolved automatically?
• Does the platform cover physical endpoints, Cloud PCs, AVD, Citrix, and other virtual environments?
These are related questions, but they do not all require the same data model.
Executive and technical perspectives
| Stakeholder | Primary question | Information required |
| CIO or CTO | Are technology issues reducing workforce productivity? | Experience trends, business impact, risk, adoption, and service improvement metrics |
| CFO or procurement leader | Are hardware investments and support costs justified? | Device performance, battery condition, failure rates, lifecycle trends, and cost avoidance |
| Digital workplace leader | Are employees receiving a consistent experience across locations and platforms? | Endpoint, application, network, collaboration, and virtual session telemetry |
| Endpoint Architect | Are devices secure, compliant, correctly configured, and operating within expected baselines? | Policy state, inventory, configuration, performance, and compliance information |
| ServiceDesk Leader | Can incidents be detected, diagnosed, and resolved before users raise tickets? | Current telemetry, historical context, guided investigation, and remediation workflows |
| Security Team | Is poor performance caused by misconfiguration, malicious activity, software conflict, or control enforcement? | Configuration, process, application, device health, security, and behavioural context |
The strategic issue is therefore not whether Intune Advanced Analytics is “good enough.” It is whether its telemetry and operational model match the outcomes the organisation expects it to deliver.
2. What Intune Advanced Analytics does well
Intune Advanced Analytics extends the existing Endpoint Analytics capabilities in Microsoft Intune. Its purpose is to help IT teams understand endpoint health, improve troubleshooting, identify trends, and make better decisions about devices and applications.
Microsoft currently describes the principal capabilities as:
• Resource performance reporting
• Battery health reporting
• Anomaly detection
• Enhanced device timelines
• Device Query
• Multi-device query
• Device scopes for targeted analytics and delegated visibility
These capabilities provide meaningful improvements over traditional inventory and compliance reports.
Resource performance
The resource performance report helps organisations identify CPU and RAM performance issues across devices, models, and manufacturers. This can support device standardisation, model comparison, hardware purchasing, refresh planning, and investigation of underperforming device cohorts.
For example, an organisation may discover that:
• A particular laptop model performs poorly under its standard application set
• Devices with lower memory configurations generate more support demand
• A business unit is operating hardware that is not suitable for its workload
• An application rollout coincides with increased resource pressure
This information is particularly valuable when combined with persona-based device requirements. Rather than applying one hardware standard across the entire workforce, IT can compare actual resource performance against the needs of knowledge workers, developers, frontline employees, mobile users, and high-performance personas.
Battery health
The battery health report provides information about battery capacity and estimated runtime. Microsoft positions the feature as a way to identify deteriorating batteries, plan replacements, make warranty decisions, and determine whether devices with healthy batteries may remain in service for longer.
This turns battery replacement from a reactive activity into a more structured lifecycle process.
From an executive perspective, the value is not limited to user convenience. Battery analytics can support:
• More accurate refresh forecasting
• Reduced premature device replacement
• Better use of warranty entitlements
• Lower disruption for mobile employees
• Evidence-based sustainability decisions
• More defensible capital expenditure requests
Anomaly detection
The anomalies report monitors application hangs, crashes, and stop-error restarts. It can also correlate affected devices using shared characteristics such as application version, driver update, operating system version, or device model.
This is useful when an issue affects a group of devices rather than a single endpoint.
For example, if devices begin experiencing application crashes after a software or configuration change, the report may help identify:
– The application involved
– The affected devices
– When the problem began
– Shared characteristics among those devices
– Other devices that may be at risk
This moves troubleshooting beyond checking devices individually and helps teams investigate patterns across the estate.
Device timeline
The enhanced device timeline provides a historical view of endpoint events. It can help administrators correlate symptoms with events such as application crashes, restarts, sign-ins, updates, or other device changes.
The timeline is particularly valuable during incident investigation because it gives the service desk a chronological view rather than an isolated point-in-time status.
However, the event timestamp and the time the event becomes available to an administrator are not necessarily the same. Microsoft notes that some analytics data is typically refreshed every 24 hours and that end-to-end latency can exceed 24 hours when event details are not uploaded immediately.
Device Query
Device Query is one of the most operationally useful Advanced Analytics capabilities.
It allows an authorised administrator to run an on-demand Kusto Query Language query against a selected corporate-owned Windows device. Intune uses Windows Push Notification Services to notify the device and expects an immediate response, provided the endpoint is online, reachable, and meets the required prerequisites.
Device Query can help support teams answer questions such as:
• Is a required service running?
• Which application version is installed?
• What is the value of a specific registry setting?
• Which processes are consuming the most memory?
• Is a required configuration present?
• Is a security or management agent operating correctly?
This can reduce the need for a remote-control session and give first-line or second-line support teams a faster path to evidence.
The important architectural point is that Device Query is on demand. An administrator initiates the query because a question or incident already exists. It is not equivalent to a continuously evaluated experience-monitoring service.
3. Understand the telemetry model
Intune Advanced Analytics combines several forms of data collection and should not be described as a single 24-hour reporting system.
A more accurate view is that it contains different operational modes.
| Intune capability | Operational model | Typical use |
| Device Query | On-demand, near-real-time query | Investigate a known device or support issue |
| Multi-device query | Query across supported device data | Inventory, exposure analysis, and fleet investigation |
| Device timeline | Historical event context | Correlate incidents with previous device events |
| Anomaly detection | Pattern and cohort analysis | Identify recurring crashes, hangs, and stop errors |
| Resource performance | Aggregated performance analytics | Compare devices, models, and manufacturers |
| Battery health | Aggregated lifecycle analytics | Replacement, warranty, and refresh planning |
| Device scopes | Administration and report filtering | Delegate visibility by team, geography, or business scope |
Microsoft states that Advanced Analytics data is usually refreshed every 24 hours, while real-time troubleshooting may require Device Query. Microsoft also notes that reporting latency can exceed 24 hours for events that are not uploaded immediately.
This creates an important distinction:
Intune can provide near-real-time answers when an administrator knows which question to ask. A DEX platform is generally designed to identify experience degradation continuously, including problems that IT has not yet suspected.
Two operating models
| Intune investigation model | DEX continuous-operations model |
| User reports an issue → service desk identifies the device → administrator runs Device Query → timeline and configuration data are reviewed → support selects an action | Telemetry is continuously assessed → degradation is detected → probable cause is identified → an automated action, technician workflow or alert is triggered → the outcome is measured |
The first model is highly useful for investigation. The second is designed for continuous detection and operational response.
A mature digital workplace may require both.
4. Where Intune Advanced Analytics reaches its limits
Intune Advanced Analytics provides genuine value, but it should not be positioned as a complete DEX platform.
4.1 Much of the analytics layer is not continuously refreshed
Microsoft states that analytics data is typically updated every 24 hours. Device Query provides the main near-real-time troubleshooting path, but it must be deliberately initiated against a reachable device.
That timing model is suitable for:
• Fleet trend analysis
• Hardware planning
• Reviewing recurring problems
• Investigating a known endpoint
• Comparing device cohorts
• Assessing the effect of a configuration change
It is less suitable when an organisation needs to detect a brief but disruptive problem as it occurs.
Examples include:
• A CPU spike during a customer presentation
• A short period of severe memory pressure
• Wi-Fi roaming instability
• A stalled logon
• A transient VPN degradation
• A delayed virtual desktop session
• A service that repeatedly fails and restarts
A daily report may confirm that degradation occurred. It may not help the support team intervene during the employee’s affected session.
4.2 Anomaly detection focuses on supported patterns
Intune’s anomaly detection monitors application hangs, crashes, and stop-error restarts, then uses correlation groups to identify shared characteristics among affected devices.
That is valuable for identifying widespread or recurring instability. It is not the same as continuously scoring the complete experience of an individual employee.
A single user may experience serious disruption without generating an anomaly that meets the platform’s pattern or severity criteria. The impact may still be significant if that user is:
• Conducting a customer call
• Processing a financial transaction
• Working in a clinical or time-sensitive environment
• Delivering an executive presentation
• Accessing a latency-sensitive virtual application
Technical severity and business impact are not always the same.
4.3 Intune remediation is available, but it is not a full telemetry-driven automation engine
It would be inaccurate to say that Intune can only restart, lock, retire, or wipe devices.
Intune supports device actions and can use remediation scripts to resolve known issues. Microsoft explicitly recommends combining Device Query, suitable remote actions, and remediation scripts within support workflows.
The more precise limitation is this:
Advanced Analytics does not provide the same always-on, closed-loop relationship between high-frequency experience telemetry, threshold evaluation, automated action, and outcome validation that specialist DEX platforms are designed to provide.
Intune remediation is well suited to:
• Detecting known configuration conditions
• Correcting registry values
• Restarting or repairing services
• Removing unwanted files
• Applying standard configuration fixes
• Resolving repeatable endpoint-management issues
A DEX automation engine may be better suited to:
• Reacting to live session degradation
• Triggering action from real-time experience thresholds
• Correlating signals across endpoint, network, application, and virtual session layers
• Applying different actions based on the user’s active application or context
• Verifying whether the user experience improved after remediation
The difference is not simply “manual versus automated.” It is the data and context that initiate the automation.
4.4 External integration options are limited
Microsoft states that Advanced Analytics does not provide a general connector for sending its data into other monitoring tools. Some functions, including multi-device query, support CSV export that can then be used elsewhere.
This matters when an organisation wants to combine endpoint analytics with:
• IT service management data
• Network monitoring
• Security information and event management
• Unified communications analytics
• Application performance monitoring
• Business service dashboards
• Observability platforms
• Employee experience surveys
CSV export is useful for ad hoc analysis, but it is not equivalent to a supported event stream or continuous observability integration.
4.5 Network and collaboration context remain separate
The primary Advanced Analytics capabilities focus on device health, configuration, resource performance, battery condition, application instability, and device investigation. Microsoft’s published capability list does not position Advanced Analytics as continuous Wi-Fi, packet-loss, jitter, or unified communications monitoring.
This can create a familiar support scenario:
• The device is compliant
• CPU and memory appear acceptable
• The application is installed correctly
• No significant crash is recorded
• The employee still has a poor Teams call
The root cause may sit outside the endpoint-management view:
• Weak Wi-Fi signal
• Access-point roaming
• Packet loss
• Network congestion
• Local internet conditions
• Peripheral problems
• Media-path degradation
• A virtual-session bottleneck
A green compliance state does not guarantee a good digital experience.
4.6 Advanced Analytics remains primarily Windows-oriented
Microsoft documents Windows-specific prerequisites for Advanced Analytics capabilities, including supported Intune-managed, co-managed, Entra-joined, and Entra hybrid-joined Windows devices. Individual features can also have additional device, ownership, build, or operating-system requirements.
Organisations should verify feature-level coverage rather than assuming that every platform supported by Intune enrolment receives the same analytics depth.
This is particularly important where the estate includes:
• macOS endpoints
• Linux workstations
• ChromeOS devices
• Azure Virtual Desktop
• Windows 365 Cloud PCs
• Citrix environments
• Omnissa Horizon
• AWS WorkSpaces
• Shared or non-persistent virtual desktops
The management plane and the experience-monitoring plane may need different coverage strategies.
5. What a dedicated DEX platform adds
A dedicated DEX platform is designed around the quality of the employee’s live interaction with technology.
A dedicated DEX platform can bring together endpoint and virtual-environment monitoring, experience scoring, remote support, automation and collaboration-service insight. The specific platform should be evaluated against organisational requirements, architecture, cost, data governance, integration needs and coverage across physical and virtual environments.
Higher-density telemetry
Many DEX platforms collect endpoint and session telemetry at much shorter intervals than traditional management reporting. This higher-density telemetry is intended to expose short-lived performance degradation that may disappear before a periodic report is generated.
That difference in sampling frequency changes what can be observed.
A high-frequency DEX model can help identify:
• Short CPU or storage spikes
• Processes consuming resources during an active incident
• Memory pressure that appears and disappears
• Network degradation during a call
• Input delay or poor session responsiveness
• A service or application failing at a specific moment
• The relationship between active application usage and device degradation
Live troubleshooting views may also expose current CPU, memory, storage, network, process and service activity, helping support teams investigate conditions while the employee is still affected.
Continuous experience scoring
A DEX score attempts to convert individual technical signals into a measure of employee experience.
Many DEX platforms calculate an experience score continuously or at frequent intervals. Scoring models can consider the duration and frequency of degradation, the technical metric involved, the employee persona, the active application and the weight assigned to each condition.
This contextual approach matters.
For example, 85 per cent CPU utilisation may be expected for a developer compiling code or a designer rendering media. The same utilisation may represent a serious problem for a contact-centre employee using a browser, telephony client, and customer relationship management application.
A meaningful DEX model should therefore consider:
• The employee persona
• The active application
• The duration of degradation
• The device specification
• The working location
• The session type
• The business criticality of the activity
Unified communications visibility
Some DEX platforms integrate with collaboration services such as Microsoft Teams to retrieve usage and call-quality information.
This type of integration can help operations teams correlate collaboration problems with endpoint and network conditions.
Instead of seeing only that a Teams call was poor, the support team may be able to investigate whether the affected experience aligned with:
• Endpoint CPU or memory contention
• Local Wi-Fi quality
• Packet loss, latency, or jitter
• A specific location or network
• A common device model
• A virtual session constraint
• An application conflict
That correlation can reduce the time spent moving between endpoint, network, collaboration, and service-management consoles.
Automation and autonomous operations
Modern DEX platforms increasingly combine continuous telemetry, anomaly detection, assisted root-cause analysis and automated remediation workflows. These capabilities should be validated through a proof of value using the organisation’s own use cases, operational controls and success criteria.
The practical operational objective is to shorten the path from detection to resolution:
| Traditional support model | DEX-led model |
| User disruption → ticket → triage → investigation → escalation → remediation → closure | Telemetry detects degradation → context identifies the likely cause → an approved action runs → experience is re-measured → a technician becomes involved only when required |
The value comes from closing the gap between “IT can see the problem” and “the employee’s problem has been resolved.”
6. Capability comparison
| Capability comparison | Intune Advanced Analytics | Dedicated DEX platform | Architectural significance |
| Configuration and compliance context | Strong, through native Intune management | Usually consumed through integration | Intune remains the authoritative management platform |
| Performance trend analysis | Strong for supported Windows analytics | Strong, often with more granular telemetry | Both can add value at different timescales |
| On-demand device investigation | Near-real-time Device Query for eligible devices | Commonly supported through live endpoint views | Intune answers known questions; DEX may expose unknown degradation |
| Continuous endpoint telemetry | Limited compared with specialist DEX sampling | Core platform capability | Important for transient and session-specific issues |
| Experience scoring | Endpoint Analytics scores and insights | Frequently continuous and context-aware | The scoring models serve different operational purposes |
| Application crash and hang analysis | Supported through anomaly reporting | Usually supported with additional live context | DEX can add process, session, and network correlation |
| Battery and lifecycle intelligence | Strong native capability | Varies by vendor | Intune may already satisfy many hardware-planning requirements |
| Wi-Fi and network experience | Not a primary Advanced Analytics capability | Common DEX use case | Important for hybrid and remote workers |
| Teams or UC quality correlation | Not a core Advanced Analytics function | Available in platforms with UC integrations | Useful where meetings and calls are business-critical |
| VDI and DaaS visibility | Not the primary focus of Advanced Analytics | Often a core strength | Critical for AVD, Citrix, Cloud PC, and mixed estates |
| Automated remediation | Available through Intune remediation and device actions | Often tied directly to live telemetry and thresholds | The trigger, context, and validation model are different |
| External observability integration | No general Advanced Analytics connector; some CSV export | Usually, broader integration and export options | Relevant to enterprise operations and service correlation |
Microsoft capability and limitation details are documented in the Advanced Analytics overview, FAQ, Device Query and anomaly guidance. DEX capabilities vary by platform and should be confirmed through supplier documentation, technical validation and a proof of value.
7. When Intune Advanced Analytics may be enough
A dedicated DEX platform is not automatically required.
Intune Advanced Analytics may provide sufficient value where:
• The estate is predominantly managed Windows endpoints
• The main objectives are device health, battery planning, configuration insight, and fleet analysis
• The support model can tolerate periodic analytics refreshes
• Device Query provides enough on-demand troubleshooting capability
• VDI or DaaS is limited or absent
• Network and collaboration telemetry is handled by other teams and tools
• Automated remediation requirements are covered by Intune Remediations
• The organisation does not need a consolidated employee-experience score
• Existing ticket volumes do not justify another platform
• Operational teams have the skills and capacity to act on the available insights
In this scenario, the priority should be to operationalise Intune rather than purchase another dashboard.
That means:
- Defining support use cases for Device Query
- Creating approved queries for first-line and second-line teams
- Establishing an anomaly-review process
- Connecting battery health findings to hardware lifecycle management
- Building remediation packages for recurring problems
- Measuring whether Advanced Analytics reduces diagnosis time and ticket demand
Licensing a capability does not create value by itself. The operational process around it does.
8. When DEX becomes strategically important
The case for DEX becomes stronger when the organisation has one or more of the following conditions.
A significant virtual desktop or Cloud PC estate
Where employees depend on AVD, Citrix, Windows 365, or another DaaS platform, the experience depends on more than the endpoint.
It includes:
• Session host performance
• Brokering
• Profile loading
• Logon duration
• Network path
• Protocol latency
• Application delivery
• Host capacity
• Storage performance
• Session responsiveness
A device-management view alone cannot represent the full service chain.
Business-critical Teams, Zoom, or contact-centre workloads
If calls and meetings are central to customer service, sales, healthcare, operations, or executive communication, collaboration quality becomes a measurable business service.
The organisation may need to identify not only that a call was poor, but why it was poor and whether the cause was the device, local network, internet path, service, peripheral, or virtual session.
Strict service-level objectives
A 24-hour analytics cycle may be unsuitable where IT is expected to:
• Detect degradation before a ticket is raised
• Restore service within minutes
• Support high-value or time-sensitive employees
• Reduce repeated incidents
• Demonstrate proactive service management
High service-desk demand
DEX may have a stronger business case where service teams spend substantial time investigating:
• Slow devices
• Application hangs
• Logon problems
• Teams quality issues
• VPN performance
• Profile problems
• High CPU or memory consumption
• Recurring service failures
These use cases can be evaluated against ticket volume, average handling time, escalation rate, and productivity loss.
A requirement for closed-loop remediation
Where the organisation wants known issues to be detected, resolved, and validated automatically, the trigger model becomes critical.
The desired workflow may be:
Detect → Diagnose → Remediate → Validate → Record → Improve
That is a broader operational model than reporting endpoint health.
9. A complementary target architecture
The strongest architectural approach is usually complementary rather than competitive.
| Microsoft Intune | DEX and operations layer | IT service management |
| Configuration, compliance, security, inventory, application delivery, Advanced Analytics and Device Query | Endpoint, session, network, application and collaboration telemetry, experience scoring, real-time detection and automation | Incidents, changes, problems, knowledge, service levels, audit records and business impact |
Role of Intune
Use Intune as the authoritative platform for:
• Device enrolment and management
• Configuration policy
• Security baselines
• Compliance evaluation
• Application deployment
• Endpoint inventory
• Device actions
• Proactive remediation of known endpoint conditions
• Advanced Analytics for supported device-health insights
Role of the DEX platform
Use the DEX platform for:
• Continuous experience monitoring
• High-frequency endpoint and session telemetry
• Network and Wi-Fi context
• Virtual desktop and Cloud PC visibility
• Collaboration-quality correlation
• Live root-cause investigation
• Threshold-driven automation
• Experience scoring by persona or service
• Validation that remediation improved the experience
Role of IT service management
Use the ITSM platform to preserve:
• Incident ownership
• Change control
• Problem-management records
• Knowledge creation
• Service-level performance
• Audit evidence
• Business-service reporting
The goal should not be to duplicate every data point across platforms. It should be to give each platform a clear responsibility and pass only the context needed for operational decisions.
10. Build the business case around measurable outcomes
A DEX investment should not be justified simply because it provides richer telemetry.
The business case should connect telemetry to measurable outcomes.
| Outcome | Example measure | Example measure Measurement approach |
| Reduce support demand | Tickets per 100 users | Compare baseline and post-deployment periods |
| Improve resolution speed | Mean time to diagnose and resolve | Measure targeted incident categories |
| Prevent incidents | Issues remediated before a ticket | Count automated actions with validated recovery |
| Improve employee experience | Time in poor experience state | Measure by persona, location, and application |
| Optimise hardware investment | Devices retained or replaced based on evidence | Connect performance and battery findings to refresh decisions |
| Improve collaboration reliability | Poor-call rate and repeat incidents | Correlate UC, endpoint, and network data |
| Improve virtual desktop performance | Logon duration, latency, session failures | Compare service levels before and after optimisation |
| Reduce operational effort | Engineer hours spent on repetitive incidents | Measure investigation and remediation effort avoided |
| Improve change quality | Experience regressions after deployment | Compare pre-change and post-change cohorts |
A proof of value should therefore establish:
- A defined set of employee personas
- A representative device and session sample
- Priority incident categories
- Current ticket and experience baselines
- Target improvements
- Approved remediation scenarios
- Data protection and governance controls
- A method for calculating financial and operational benefit
11. A practical decision framework
Use the following questions before deciding whether Advanced Analytics is sufficient.
| Assessment question | If the answer is “yes” |
| Do we need to identify problems while users are actively experiencing them? | Evaluate high-frequency DEX telemetry |
| Do we operate AVD, Citrix, Windows 365, or another DaaS platform at scale? | Include session and virtual-infrastructure monitoring |
| Are Teams or other collaboration services business-critical? | Include UC and network-quality correlation |
| Do we need automatic action based on live experience thresholds? | Evaluate telemetry-triggered DEX automation |
| Is our endpoint estate broader than the supported Advanced Analytics scope? | Validate cross-platform DEX coverage |
| Do support teams already have enough information once a ticket is raised? | Focus on proactive detection rather than additional investigation tools |
| Are battery, hardware, compliance, and configuration health the main priorities? | Intune Advanced Analytics may be sufficient |
| Can existing Intune Remediations resolve the majority of repeatable issues? | Optimise the current Intune operating model first |
| Can we demonstrate ticket reduction or productivity improvement from DEX? | Build a formal proof of value |
| Would a second platform add cost without changing operational processes? | Avoid tool acquisition until ownership and workflows are defined |
Conclusion: Better analytics do not remove the need for telemetry depth
Intune Advanced Analytics materially strengthens Microsoft’s endpoint-management proposition. It brings device-health insight, fleet analysis, historical context and on-demand investigation much closer to the teams already managing the estate.
But it is not a complete substitute for DEX. Its strongest use cases are management context, lifecycle insight, supported anomaly analysis and investigation of known questions. A dedicated DEX platform is designed for continuous monitoring, transient issue detection, cross-layer correlation, virtual-session visibility and telemetry-driven remediation.
The strategic question is not whether to choose Intune or DEX. It is whether the organisation’s priority is endpoint visibility, live experience assurance, or a combination of both.
For many organisations, the strongest architecture will use Intune as the authoritative platform for endpoint management, security, compliance, configuration and device-health analytics, while using DEX where real-time monitoring, session awareness and closed-loop remediation are genuinely required.
