Your Dynamics 365 data platform, kept running, and still yours

Break/fix waits for a pipeline to break and reacts to a ticket; a managed data service is proactive and continuous, so problems are prevented, not just fixed. It monitors extraction, keeps the warehouse healthy, manages Fabric capacity to cost, keeps the numbers reconciling and keeps the platform current with Microsoft change, which is the difference between a support inbox and a data platform that stays reliable.

The sharpest run-state question is whether a managed service is just a support inbox with a nicer name. It is not, and that is exactly why a recurring bill is worth paying. A support contract is reactive: it sits quiet until a refresh fails or the warehouse goes stale, then someone raises a ticket and someone else reacts, usually after a number was already wrong.

A managed service inverts that. The work happens before anything breaks, absorbing Microsoft's platform changes and the quiet decay that a Delta-based warehouse suffers when nobody is maintaining it. The point is not to fix faster. The point is that far less breaks.

• Break/fix. Waits for a failure. Reacts to a ticket. Fixes the symptom. The platform decays between incidents, and the decay is invisible until a figure is wrong at month-end.
• Managed service. Watches the platform continuously. Prevents the failure. Keeps the pipelines, the warehouse, the capacity, the governance and the reconciliation current, so month-end is quiet by design.

For the decision itself, laid out plainly, talk to us about a managed data service versus a support contract.

A managed data service for Dynamics 365 keeps your data platform reliable, governed and reconciling to your Dynamics data. It includes proactive extraction and pipeline monitoring, warehouse and lakehouse maintenance, Fabric capacity managed to cost, recurring data-quality and reconciliation checks, data-layer governance upkeep, and keeping the platform current with Microsoft's stack. It is one continuous service, not a menu of one-off jobs.

Here is the whole of what the retainer covers, so there is no question about what the monthly fee buys.

• Extraction and pipeline reliability. Getting Dynamics data into the warehouse now runs through Dataverse, whether by Azure Synapse Link or Link to Microsoft Fabric. We keep whichever path you are on running, with alerting across the whole estate rather than a person watching an inbox, catching a broken or throttled link before the warehouse goes stale, and handling the Dataverse-storage consumption the Fabric link adds.
• Warehouse and lakehouse health. A Delta-based warehouse degrades unless it is actively maintained. We run the OPTIMIZE and VACUUM cadence, keep table layouts tuned as data volume changes, and hold the warehouse-versus-lakehouse split where it belongs, so scans stay fast and storage does not quietly accumulate stale files in OneLake.
• Capacity managed to cost. Fabric capacity watched and tuned, reserved against your real cadence and flexed for the peaks, with autoscale billing for elastic Spark workloads and throttling and overage watched so the bill does not run away. This seeds the cost-control section below.
• Data quality and reconciliation. Recurring reconciliation and data-quality checks, row-count and control-total checks against source, referential integrity, and catching a refresh that completed but silently dropped rows, so the numbers keep reconciling to your Dynamics financial dimensions, eliminations and multi-entity roll-up.
• Governance as a service. Federated domain and workspace ownership kept accurate, access reviews run on a cadence, endorsements kept current, and sensitivity-label, tagging and data-location hygiene maintained, so the platform stays governable by a team, not a person.
• Kept current with Microsoft. We track the Fabric and Dynamics data roadmap and absorb the re-plumbing when Microsoft moves, as it did retiring Export to Data Lake, so the platform never falls behind a deprecation or a consumption-rate change you did not see coming.

We manage your Fabric capacity to cost, reserving the predictable base and flexing the peaks, moving elastic Spark workloads to autoscale billing, and watching throttling and overage so the spend stays controlled rather than creeping. The result is a predictable monthly cost, tailored to your platform and shown before you commit.

This is where a managed service most visibly beats a build or an in-house team, because Fabric capacity is a continuous, cost-sensitive decision that a small data team cannot sustain, and getting it wrong either throttles the pipelines or wastes the budget.

Capacity to cost. Fabric capacity is not a fixed line on a bill, it is a lever. On the current SKUs, capacity can be paused, resumed and resized on demand, so we reserve the predictable base and flex the peaks, scaling up for a heavy load and back down after, and automating the schedule so it tracks your real cadence. Elastic Spark and data-warehousing workloads move to autoscale billing so you pay for the burst, not a reserved peak. Overage is charged at a multiple of the normal rate, so we watch utilisation against a threshold and act before it tips, rather than reading it on the invoice.

Where a pre-built, pre-reconciled foundation fits under a managed platform, Reveal is our productised option, which reduces implementation time and risk.

Your data platform comes under management through a platform review or a build handover, then runs on a continuous rhythm: monitored, maintained, kept current with Microsoft change and reviewed with you on a regular cadence. The service is offered in tiers matched to how much coverage your platform needs, and the shape is agreed before you commit.

This is a real, worked service with a rhythm to it, not a monitoring dashboard you never see. Here is how a platform comes under management, and what the ongoing cadence looks like.

1. Assess and onboard

   A platform review or a build handover brings the platform under management. We baseline the figures that have to reconcile and the current governance state, so we run against real targets from day one, not assumptions.

2. Monitor and run

   Centralised extraction, capacity and governance monitoring, the proactive core, so decay is caught early and the platform stays reliable between the peaks and the platform changes.

3. Optimise and keep current

   Continuous warehouse maintenance, capacity managed to cost, the Microsoft roadmap tracked, and governance kept clean, the ongoing hygiene that stops a governed platform drifting out of governance.

4. Review and improve

   A regular cadence with you, reliability, cost, reconciliation and what improved, so the platform gets quietly better over time and you can see the service earning its place.

The service comes in a tiered shape, so you fund the level of coverage your platform actually needs.

• Good. The reliable core, proactive monitoring and the essential maintenance, governance and cost upkeep that keeps the platform trustworthy.
• Better. The core plus a fuller optimisation and governance cadence and more included expert time, for a busier or more critical platform.
• Best. The fullest coverage, the widest monitoring scope, the most frequent optimisation and the most included expert time, for a platform the business runs on.

Each tier is tailored to your platform and defined before you commit.

A managed data service is the top rung. A platform review can route an existing warehouse in, assess, then run; a build hands over into it, build, then run; and advisory and governance sit beside it as the next step, run, then mature. You choose each rung on the evidence, with no obligation.

1. Assess first.

   If you have a warehouse someone else built, or inherited, start with a data platform review, which assesses it and routes it into the run-state.

2. Or build first.

   If you are still building the foundation, a Dynamics 365 data warehouse build hands over documented and governed, straight into managed, with no gap where the platform starts to decay. See the Data Warehouse for Dynamics 365 programme for how the build works.

3. Then run it.

   This page: the platform run reliably, on a monthly service, so the numbers stay trustworthy without you chasing them.

4. Then mature it.

   When you want to govern, optimise or extend further, data advisory and governance sits beside managed as the next step. Talk to us about the next step.

For the full picture of the programme this service sits inside, see Data Warehouse for Dynamics 365.

This service runs the data layer. Managed BI for Dynamics 365 runs the reports and the semantic model on top: we keep your data reconciling, and Managed BI keeps your reports reliable on top of it. Take one, the other, or both.