Define enterprise data and AI vision, strategy and roadmap — align with business objectives and identify high-value AI and analytics use cases

Design and implement modern cloud-native data platforms — consolidate fragmented reporting and analytical environments

Design and implement end-to-end Microsoft Fabric platforms including OneLake, Data Factory, Data Engineering, Data Science and Real-Time Analytics

Implement Power BI reporting, dashboards and self-service analytics — define KPI frameworks and management reporting

Establish data governance frameworks — data quality, metadata, lineage, stewardship and Master Data Management (MDM)

Define AI adoption strategy — implement Generative AI solutions, copilots and AI-assisted decision-making with responsible AI controls

Data & AI Strategy

Data Transformation Roadmap

Microsoft Fabric Architecture & Implementation Blueprint

Enterprise Data Architecture

Lakehouse Architecture Design

Data Governance Framework

Data Operating Model

Data Quality & Master Data Strategy

Power BI Reporting & Analytics Framework

AI Adoption Strategy

AI Governance Framework

Generative AI Use Case Portfolio

Real-Time Analytics Architecture

Improved data-driven decision-making

Faster access to trusted and actionable business insights

Reduced complexity across reporting and data platforms

Increased operational efficiency through automation and AI

Enhanced customer experience through personalization and predictive insights

Better data quality, governance and ownership

Scalable foundation for AI and advanced analytics

Reduced cost and complexity of legacy data environments