Microsoft Fabric Accelerator
Get more from your data, faster
The MPowerUp Fabric Accelerator helps organisations unlock the value of their data faster. By connecting your core business applications to Microsoft Fabric in days rather than weeks, the Fabric Accelerator builds the foundation for a trusted data layer, without the cost and complexity of building pipelines from scratch.
A 'configuration not code' approach means quicker onboarding of new data sources, while built-in features such as PII masking, data quality and validation, full and incremental loads, and enhanced logging ensure quality and control at every step.
The Fabric Accelerator is a ready-built platform that standardises how data is brought into your organisation.
Rather than building custom pipelines for every data source, the platform uses configuration to control how data is ingested, validated, and transformed. This creates a repeatable, scalable approach that supports growth without increasing complexity.
It is designed specifically for Microsoft Fabric and follows a structured medallion architecture (Bronze, Silver, Gold) – a proven pattern for organising data from raw ingestion to trusted, reporting-ready outputs.
What it is
A strong foundation for reporting
When data is fragmented across multiple different systems, every report becomes a manual exercise.
The MPowerUp Fabric Accelerator centralises your data into one governed platform with consistent definitions, automated quality checks, and a clear lineage from source to report.
You get a trusted data layer and reports you can rely on.
A practical foundation for AI
The MPowerUp Fabric Accelerator provides consistent, quality-checked data, clear lineage, and proper governance that gives you an AI-ready data platform and the foundation to explore machine learning and advanced analytics.
The outcome
A governed, scalable data platform in Microsoft Fabric that enables faster data integration, more reliable reporting and a stronger foundation for analytics and AI.
The trusted data layer
Trust in data comes from knowing where it came from, what has happened to it, and who can see what.
Full
audit trail
Every pipeline run, every record processed, every change logged automatically
Configurable PII masking
Sensitive fields are protected using rules you define once and apply consistently across the platform
Data quality
gates
Records are validated before they are promoted, so problems are caught early rather than surfacing in reports
Consistent
schemas
Data follows the same structural patterns regardless of where it came from, giving downstream consumers a stable interface to build on
The Fabric Accelerator builds that trust in from the start:
What's Included
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Automated orchestration of data pipelines and scheduling
Full and incremental loads
Built-in logging, monitoring, and auditing
Data validation and data quality rules
Configurable PII data masking
Standardised medallion architecture alignment
Foundations for lineage and governance
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Why choose the Fabric Accelerator?
Faster onboarding of data
Bring new data sources into your platform in days rather than weeks or months, without rebuilding pipelines each time.
Governance from day one
Establish consistent logging, auditing, and control as part of the platform, not as an afterthought.
Accelerated time to value
Start with a working foundation rather than building from scratch - reducing delivery time and dependency on specialist skills.
Reduced delivery risk
A proven, repeatable framework that removes reliance on bespoke development and reduces failure points.
Scalable by design
A single, unified data platform that can grow with your organisation without needing to be re-engineered.
When it’s the right fit
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The Fabric Accelerator is particularly valuable when:
Your organisation looking to build a trusted data layer
You require a foundation for Reporting and AI
Data is fragmented across multiple systems
Previous data platform initiatives have stalled or underdelivered
New data sources take too long to onboard
There is heavy reliance on bespoke pipelines or specialist engineers
Data governance is inconsistent – there is no clear audit trail, no standard approach, and sensitive data isn’t consistently protected
A “single source of truth” has been difficult to achieve in practice