10decodersOne governed foundation for banking analytics
A regional bank serving retail, corporate and private banking clients needed its data in one consistent, secure, traceable place for reporting and regulatory analytics. 10Decoders is building an Azure data platform on a three-layer Medallion architecture, with a BIAN-aligned data model, governed Power BI reporting and role- and attribute-based access control.
Reliable data for a regulated bank
In banking, every report, dashboard and regulatory submission depends on the data underneath it. This bank's data needed a common structure, consistent business definitions, clear lineage and tight control over who can see sensitive financial information — without breaking the Power BI reports teams already relied on.
10Decoders is building a modern data analytics platform on Microsoft Azure. Data flows through Bronze, Silver and Gold layers into a BIAN-aligned model and standardized Power BI semantic layer, with Microsoft Purview providing catalog, glossary, lineage and data quality monitoring. Releases R1 to R3 are now in UAT, loading data daily on the new model.
The platform, layer by layer
Azure Data Factory
Pipelines move data into the platform and carry it from Bronze to Silver to Gold.
Medallion Layers
Raw, refined and curated data kept in separate, clearly defined stages.
BIAN-Aligned Model
An industry-standard financial services structure for representing banking data.
Power BI Semantic Models
One shared layer for standard reports, executive dashboards and self-service analysis.
Microsoft Purview
Data catalog, business glossary, lineage tracking and data quality monitoring.
RBAC & ABAC
Access granted by role and by attribute, so sensitive data reaches only the right people.
Reporting is only as trustworthy as the data underneath it.
The Challenge
- Banking data arrived from many sources with no common structure.
- Business definitions could differ from one report to the next.
- Existing Power BI reports had to keep working through the transition.
- Limited visibility into data lineage, quality and ownership.
- Sensitive financial data needed strict, auditable access control.
Our Approach
- Land all source data in a Bronze layer through Azure Data Factory.
- Standardize on a BIAN-aligned model and one Power BI semantic layer.
- Repoint existing reports to the new semantic layer for continuity.
- Catalog, glossary, lineage and quality checks in Microsoft Purview.
- Role- and attribute-based access controls across the platform.
The Solution
Source data lands in the Bronze layer as-is. Azure Data Factory pipelines then map, transform and validate it into the Silver layer, aligning it with the BIAN-based financial services model, and curate it into an analytics-ready Gold layer.
From Gold, Power BI semantic models give analysts and executives one consistent set of business definitions. Purview tracks where every data asset came from and how healthy it is, while RBAC and ABAC decide who can see what. Releases R1 to R3 are running in UAT with daily data loads; production deployment follows the client's sign-off.
Layered data pipelines
Ingestion, standardization and curation as separate, maintainable stages.
One version of the numbers
Shared Power BI models behind standard reports and executive dashboards.
Traceable data assets
Catalog, glossary, lineage and quality monitoring in Microsoft Purview.
Controlled access
RBAC and ABAC protect sensitive banking information by role and attribute.
From source systems to governed insight
Banking Source Data
Retail, corporate and private banking data ingested into the Bronze landing layer.
Medallion Platform on Azure
Silver and Gold processing onto a BIAN-aligned model, governed by Purview.
Reporting & Analytics
Power BI semantic models, executive dashboards and self-service analysis.
Built for a regulated environment
Clear separation of stages
Raw, refined and curated data each have one job, which keeps pipelines easy to follow and maintain.
An industry data model
A BIAN-aligned model gives banking data a familiar, consistent shape across business domains.
Shared business definitions
One semantic layer means reports and dashboards draw on the same definitions.
No forced report rebuilds
Existing Power BI reports are repointed to the new layer rather than rebuilt from scratch.
Lineage you can follow
Purview shows where data came from, what it means and whether it passes quality checks.
Fine-grained access
Role- and attribute-based rules match data access to business and governance needs.
Four parts of one platform
Medallion Data Pipelines
Azure Data Factory ingestion plus Bronze-to-Silver and Silver-to-Gold processing.
BIAN-Aligned Data Model
A financial services data model that organizes banking data for analytics and reporting.
Power BI Semantic Layer
Semantic models, executive dashboards and existing reports repointed to the new layer.
Governance & Access Controls
Purview catalog, glossary, lineage and quality monitoring, with RBAC and ABAC security.
What changes for the bank
A structured data foundation
Banking data moves through defined raw, refined and curated layers instead of ad-hoc processing.
Consistent numbers in reporting
A BIAN-aligned model and shared semantic layer give every report the same definitions.
Continuity for existing reports
Current Power BI reports are repointed to the new layer, so teams keep the reports they rely on.
Visible, traceable data
Catalog, glossary, lineage and quality monitoring make data assets easy to find and follow.
Stronger access management
RBAC and ABAC bring structured control to sensitive banking data.
Room for future analytics
The layered design and standard model can extend to new dashboards and analytical use cases.
How the work is delivered
Delivery Quality
- Phased releases: R1, R2 and R3 migrated from Dev to UAT.
- Data loaded into UAT daily on the new model for validation.
- Production deployment follows client sign-off after testing and UAT.
Team & Engagement Model
- Cross-functional team spanning architecture, data modeling, development, DevOps, QA and business analysis.
- Phased delivery, with each release validated before the next.
- Discovery and implementation planning for further analytical use cases.
Governance & Security
- Microsoft Purview catalog, glossary, lineage and data quality monitoring.
- RBAC and ABAC controls for sensitive financial information.
- Standardized engineering patterns across every pipeline stage.
Value for every team
Analytics-ready data
A structured Gold layer and shared semantic models let analysts spend time on results, not on reconciling data.
One consistent view
Executive dashboards and standard reports draw on the same definitions across banking domains.
Traceable, governed data
Catalog, lineage and quality monitoring support governance and regulatory and compliance analytics.
