Connect QAD ERP to Microsoft Fabric with Open Mirroring
Building and maintaining your own QAD connection to Fabric takes data team time away from reporting. Kanerika's ready-built QAD integration brings data from all your QAD databases into Microsoft Fabric through Open Mirroring and keeps it current for Power BI reporting and analytics.
Get Started with QAD to Fabric Mirroring
The ERP Data Challenge
The Cost of Leaving Your QAD Data Disconnected
23%
of manufacturers have fully integrated their ERP, PLM, quality and OT systems.
44%
of manufacturers aren’t effectively using the data they already collect
90%
of IT leaders say data silos are creating business challenges
$12.9M
is the average yearly cost of poor data quality to an organization
QAD Open Mirroring for Microsoft Fabric
QAD runs on the Progress OpenEdge database, and getting its data into Fabric takes QAD-specific handling. Kanerika's accelerator reads from your QAD databases and sends changes to Fabric through Open Mirroring, Microsoft's own method for bringing other systems into Fabric.
Multiple QAD Databases
Each QAD database keeps its own space in Fabric, so plants and regions stay organized.
Deleted Records
Records removed in QAD are removed in Fabric too, so reports match the source.
Accurate Data Types
Field types come straight from QAD’s own definitions, which avoids load errors.
Continuous Sync
Mirroring keeps running through quiet periods when nothing has changed in QAD.
See How QAD ERP to Microsoft Fabric Open Mirroring Works
Watch how Kanerika connects to your QAD databases, brings data into Microsoft Fabric through Open Mirroring, and keeps it current for Power BI reporting and analytics.
Start with a QAD Readiness Assessment
In 2 to 3 weeks, you’ll know what it takes to bring your QAD data into Fabric, before you commit to a project. You’ll come away knowing which QAD data is ready to move, what needs fixing first, how fresh the data in Fabric can be, what Fabric capacity to plan for
The Mirroring Process
How Our QAD to Microsoft Fabric Process Works
QAD Readiness Assessment
In 2 to 3 weeks, we review your QAD setup and list every database and table in scope. We check which tables track changes reliably and which need fixes before they can sync. Then we estimate data freshness and Fabric capacity, and agree the right ingestion approach with your team.
Pilot on Your Own QAD Data
We connect one QAD module or region to Microsoft Fabric using your own data, with a fixed scope agreed up front. The accelerator, mirrored database and SQL endpoint are all set up. We then check record counts against QAD and review the results with your team before deciding next steps. See how this worked on a client’s live QAD systems.
Scale by Module and Region
After the pilot, we add more QAD databases, modules and regions on the same accelerator, so nothing is rebuilt. What the pilot showed about data volumes and refresh times shapes sizing for each step. Fabric capacity is reviewed as the estate grows, and each module or region is priced separately.
Run and Support
After go-live, the sync is monitored and every run is logged, with alerts on errors. Regular record-count checks against QAD confirm the numbers match. When a QAD upgrade changes your data structure, the changes go through a managed process. Ownership, support levels and escalation paths are agreed with your team.
The QAD to Fabric Advantage
What Enterprises Gain with QAD Data in Microsoft Fabric
One View Across Plants
- Data from every QAD database, across plants and regions, lands in OneLake as one shared source for reporting.
- Finance, operations and supply chain teams can compare sites side by side in a single Power BI view.
- Each QAD database keeps its own space in Fabric, so regional data stays organized and easy to trace.
Latest Data Without Custom Build
- Open Mirroring keeps QAD tables up to date in Fabric, so reports reflect what is happening in QAD.
- New, changed and deleted QAD records all carry through to Fabric, so the numbers match your source system.
- Your data team doesn't have to build the QAD connection, so more time goes into reporting and analytics.
Less Strain and Less Risk
- Where QAD tables support it, only changed records are read each cycle, keeping the load on QAD light.
- Re-running a load gives the same result every time, with no duplicate rows showing up in your reports.
- If one table looks wrong, only its affected time range is processed again, so nothing else needs reloading.
Built-In Power BI, Analytics and AI
- Build Power BI reports on QAD data in Fabric, with no file exports or separate extracts to maintain.
- Query QAD data with SQL, or open it in Fabric notebooks for deeper analysis and data science work.
- Combine QAD data with data from your other business systems to build a single base for AI projects.
Case studies
Delivering Measurable Outcomes
For a global electronics manufacturer, we brought 500 source tables from ten regional QAD databases across Asia Pacific, Europe and the Americas into one governed Fabric layer. The first working environment ran on real production data within 10 weeks.
60% Faster Migration: Crystal Reports to Power BI
Impact:
- 60% Faster Migration
- 10x Data Scale
- 99.5% Refresh Success Rate
60% Faster Analytics with Informatica to Alteryx
Impact:
- 45% Faster Reporting Cycles
- 38% Reduction in Maintenance Costs
- 60% Improved Analytics Turnaround
74% Faster Retail Reporting with Microsoft Fabric
Impact:
- 74% Faster Reporting Cycles
- 65% Increase in Reporting Stability
- 72% Faster Access to Current Metrics
Frequently Asked Questions (FAQs)
Does Microsoft Fabric support QAD mirroring natively?
No. Fabric’s built-in sync covers systems such as SQL Server, Oracle, SAP Datasphere and Snowflake, and QAD isn’t one of them. For other systems, Microsoft offers Open Mirroring, which lets a partner like Kanerika build the connection. Our technical guide to mirroring QAD data into Microsoft Fabric covers how the connection works.
What does the QAD readiness assessment cover?
In 2 to 3 weeks, Kanerika reviews your QAD setup and lists every database and table in scope. It checks which tables track changes reliably and which need fixes, estimates data freshness and Fabric capacity, and agrees the ingestion approach with your team, before you commit to a project.
How long does a QAD to Microsoft Fabric project take?
The readiness assessment takes 2 to 3 weeks. Pilot and rollout timelines depend on how many QAD databases, modules and regions are in scope, and the assessment sets them.
How much does QAD to Microsoft Fabric mirroring cost?
Cost depends on how many QAD databases, tables and modules are in scope. The pilot is scoped per customer, and rollout is priced by module or region once the assessment has sized your estate.
Does QAD keep running as usual while data syncs to Fabric?
Yes. QAD stays your ERP. Our accelerator reads data from QAD and sends the changes to Fabric, and where tables support it, only changed records are read.
Does it work across several QAD databases, sites and regions?
Yes. Each QAD database gets its own connection and its own space in Fabric, so data from different sites stays organized. The readiness assessment sizes the whole setup first, since more databases and tables need more Fabric capacity.
How current is the data in Fabric?
Freshness depends on how often changes are read, how many tables and databases are in scope, and the Fabric capacity behind them. The readiness assessment estimates latency for your estate.
What happens when we upgrade QAD?
When a QAD upgrade changes the structure of your data, such as adding new fields, those changes go through a managed process during the Run and Support phase, agreed with your team.
What does the pilot include?
The pilot connects one QAD module or region to Microsoft Fabric using your own data, with a fixed scope agreed up front. Kanerika sets up the accelerator, the mirrored database and the SQL endpoint, checks record counts against QAD, and reviews the results with your team before you decide on rollout.
What if a load fails or the data looks wrong?
Every run is logged, and errors trigger an alert. Re-running a load doesn’t create duplicates, and if one table looks wrong, only that part is reloaded. We also recommend regular record-count checks against QAD.