How Embee Software designed a Microsoft Fabric, Azure, and Power BI analytics platform for a leading wealth management firm to unify diverse data sources into a governed, cloud-native lakehouse with ML and AI-driven reporting.
The Challenge
The customer, a leading Indian wealth management and investment research firm, operates in a data-intensive, regulated environment, with information scattered across many systems and a heavy reliance on manual reporting.
It needed to unify structured, semi-structured, and unstructured data into a single, governed analytics platform that could scale and support predictive, AI-driven insight.
The core gaps:
- Fragmented data spread across databases, SaaS apps, flat files, FTP, and APIs, making integration and analysis difficult
- Heavy reliance on manual data preparation and reporting, causing inefficiency, delay, and human error
- Limited scalability from on-premises infrastructure unable to grow with analytics workloads
- Reporting tied to individuals, creating bottlenecks and limiting agility
- Inconsistent KPIs and reporting standards across the business
- A need for secure, role-based access and compliance with data-governance policies
The opportunity was to move the firm from reactive, manual reporting to predictive, automated analytics on a single governed platform, integrating ML and AI to accelerate reporting cycles and improve accuracy.
The Solution
Embee Software designed an enterprise data analytics platform built on Microsoft Fabric, Azure Data Services, and Power BI, unifying structured, semi-structured, and unstructured sources into a scalable Lakehouse and Data Warehouse architecture, with semantic layer powering advanced Power BI analytics.
What the platform delivers:
- Unification of structured, semi-structured, and unstructured sources, including Oracle, SQL, PostgreSQL, Tally, Zoho, Salesforce, and Bloomberg feeds, among others
- A scalable Lakehouse and Data Warehouse architecture for diverse data requirements
- Seamless data ingestion, transformation, and modelling across all integrated sources
- A semantic layer driving advanced Power BI dashboards and reports
- ML and AI automation: ML detects patterns and anomalies, while AI generates narrative summaries, automating data extraction, validation, and report generation
- A cloud-native design ensuring scalability, flexibility, and strong governance
Microsoft products & services: Microsoft Fabric (Lakehouse and Data Warehouse), Azure Data Services, and Power BI, with role-based access controls and India data residency for compliance.
What makes Embee Software’s approach different:
- Deep expertise in Microsoft Fabric, Power BI, and governance-focused delivery
- A unified architecture spanning structured, semi-structured, and unstructured data
- ML and AI built into the reporting layer, not bolted on, moving the business toward predictive analytics
- A cloud-native foundation designed for scalability, flexibility, and compliance
Results & Impact
| Metric | Detail / Outcome |
| Data sources unified | Oracle, SQL, PostgreSQL, Tally, Zoho, Salesforce, Bloomberg, and more |
| Platform | Microsoft Fabric Lakehouse + Data Warehouse with a semantic layer |
| Analytics | Advanced Power BI dashboards on a governed semantic model |
| Intelligence | ML pattern/anomaly detection and AI-generated narrative summaries |
| Governance | Role-based access, India data residency, advanced security |
Anticipated outcomes for the firm:
- Faster decision-making, with real-time analytics reducing turnaround for actionable insights
- Operational efficiency, as automated ETL/ELT minimises manual effort and frees up resources
- Scalability and flexibility, with a cloud-native architecture that grows with business needs
- Governance and compliance through role-based access, India data residency, and advanced security
- Improved productivity, with self-service access to accurate, timely reports
- Enhanced reporting, as ML and AI automation improve clarity, accuracy, and speed for proactive planning
The ML & AI Angle
Manual reporting is repetitive and error prone. By embedding ML and AI, the platform automates data extraction, validation, and report generation: ML algorithms detect patterns and anomalies, while AI-powered tools generate narrative summaries.
This accelerates reporting cycles, improves accuracy, and moves the firm from reactive to predictive, data-driven decision-making.
Why the Firm Chose Embee Software
- Proven expertise in Microsoft Fabric, Power BI, and governance-focused delivery
- The ability to unify diverse, hybrid data sources into a single platform
- ML and AI capability that turns reporting from reactive to predictive
- A cloud-native approach engineered for scalability, flexibility, and compliance
Repeatability: The solution is built from reusable assets, including pre-built data pipelines, semantic models, and KPI frameworks tailored for financial analytics, making it readily deployable for similar BFSI, wealth-management, and investment-research firms.
Turn Fragmented Data into Governed, AI-Ready Insight
Most enterprises do not have a data problem so much as a fragmentation problem: the numbers exist, but they live in different systems, owned by different people, reconciled by hand.
Embee Software builds unified analytics platforms on Microsoft Fabric, bringing lakehouse, warehouse, semantic modelling, and data analytics into one governed platform, with data protection and data integrity designed in from the start.
As a Microsoft Fabric Featured Partner and Microsoft Frontier Partner, we help regulated BFSI organisations move from manual, person-dependent reporting to automated, predictive analytics, supported by cloud consulting and assessment and Azure cloud services. Browse more customer success stories.
Want to see what a governed data platform would look like for your business? Book a consultation with our Data and AI team.
