Bridging Data Gaps with Centralized BI for 2000+ Users

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centralized fact table
0 B+
reports integrated via
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business units unified
via one single app
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Client: Uniqa
Industry:
Technology: Microsoft Power BI, SQL Server
Duration: 12 months

Client Background

UNIQA is a leading insurance group operating across Central and Eastern Europe, offering a wide range of insurance and financial services to individuals and businesses. The company focuses on innovation, customer-centricity, and long-term sustainability in delivering its services. 

Challenges

Uniqa sought to enhance its Business Intelligence capabilities through Microsoft Power BI, SQL Server, and Azure. Operating across multiple regions, the company required a scalable and secure BI solution.   

The 12-month project focused on data consolidation, report automation, and improved governance to support data-driven decision-making.  Key challenges included:  

Lack of Standardized Reporting 
No unified reporting framework from visual & data sources perspective. 

Data Fragmentation 
Disconnected systems made it hard to align business metrics. 

Isolated Data Silos 
Data from 8+ systems needed to be consolidated into a single data model.

Scalability 
Missing efficient process handling large tabular data, including 1.8B+ row fact table.  

Missing Governance in Self-Service 
Users lacked access to a controlled, validated data model.

Security Gaps 
No row-level access controls for sensitive business data. 

Absence of Development & Deployment Process 
BI assets lacked proper versioning and controlled release processes. Decentralized development with no coordination of work across departments.  

Our Solution

To address these challenges, we:   

Implemented Standardized Reporting 
Design of unified reporting layout and centralization of reports into one Power BI App accessed by 200 internal users and 2000 external insurance agents.   

Resolved Data Fragmentation 
Developed a centralized BI model with incremental loading for fact tables and full loads for dimensions to optimize performance.   

New Data Model 
8+ systems integrated into a consolidated semantic layer leveraging Power BI Premium service. 

Achieved Scalability 
Data load was made possible with custom incremental data processing and partitioning enabled us to handle large volumes of data. Relational and semantic layer based on column store technology.  

Established Governed Self-Service 
Creation of 1 consolidated model serving as single source of truth enabling both self-service & standard reports.    

Closed Security Gaps 
Deployed row-level security to enforce role-based data access.   

Introduced Development & Deployment Process 
Used Git for version control, PBIP/TMDL developer mode, and Power BI deployment pipelines to centralize development and release management in the most efficient way.

Outcomes

Enhanced Data Accessibility 
Centralized models provide frequent and trusted insights for business users.  

Improved Efficiency 
Optimized data availability, regular users now have up-to-date information every morning instead of every couple of days, weeks or even a month.  

Stronger Data Governance 
Enforced data validation and security measures.  

Streamlined Development 
Git versioning and deployment pipelines ensured controlled and efficient releases.  

Cost Savings 
Decommissioned redundant BI models, reducing maintenance overhead.  

At a Glance

Through the strategic implementation of Microsoft Power BI, SQL Server, and Azure, the company transformed its Business Intelligence capabilities, achieving better data integration, security, and decision-making efficiency. 

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