We modernize monolithic on-prem legacy databases and data warehouses by migrating to Azure-native services like Azure SQL, PostgreSQL, Cosmos DB, Databricks, or Microsoft Fabric, depending on performance, compliance, and global access requirements.
This shift reduces query latency, eliminates licensing complexity, and improves reliability, availability, and resilience while reducing operational overhead.
We design and implement scalable enterprise data lakehouses on Azure Data Lake Storage Gen2 and OneLake, centralizing fragmented structured, semi-structured, and unstructured data assets from ERP, CRM, IoT, and external sources.
This enables consistent, secure, and performant access to raw and curated data for advanced analytics, regulatory reporting, or AI training pipelines across your enterprise.
Enable real-time operational dashboards, predictive analytics, and AI-powered reporting with Azure Synapse Analytics, Microsoft Fabric, and Power BI.
We help you reduce report generation times and enable business users to access insights on demand—whether it's factory-level KPIs in manufacturing, store-level sales trends in retail, or customer transaction trends in BFSI.
We implement and optimize Azure Databricks environments for big data processing, machine learning model training, and AI deployment - improving data engineering speed, model training, and pipeline reliability.
This includes CI/CD for ML, workspace governance with Unity Catalog, and integration with Fabric, Azure Databricks, Azure OpenAI, Synapse Analytics, and OneLake/Data Lake.
Orchestrate, transform, and automate ETL/ELT pipelines using Azure Data Factory and Event-Driven Architectures, reducing reliance on manual data wrangling and improving data freshness for analytics and AI use cases.
For example, automatically ingesting and transforming POS, inventory, or sensor data for near real-time visibility.
Implement enterprise-wide data governance with Microsoft Purview, enabling data discovery, classification, lineage, and access control to support compliance and secure data usage.
This is critical for regulated industries and organizations operating across multiple geographies. We help you enforce consistent policies for PII, GDPR, and internal controls while improving data transparency for business users and customers.
Reduce total cost of ownership across your Azure data ecosystem by right-sizing storage, optimizing compute usage, and automating scaling policies.
We apply FinOps principles across services like Data Lake, Fabric, Synapse Analytics, Databricks, and Cosmos DB, helping data leaders maintain performance while controlling spend—especially in high-volume environments like supply chains, retail analytics, or sensor-heavy operations.
Transform legacy systems into cloud-native, high-performance applications.
Whether migrating to the cloud, going multi/hybrid-cloud, or optimizing existing infrastructure, we help you re-architect, containerize, and optimize workloads for cloud-native applications that enhance performance, security, and cost-efficiency; while providing fast, responsive experiences.
Optimize containerized applications with Azure Kubernetes Service (AKS).
We help deploy, scale, and manage microservices efficiently, reducing infrastructure complexity and deployment times.
Leverage .NET, Microsoft’s development framework, seamlessly integrated with Azure.
As a Microsoft Solutions Partner, we specialize in .NET Core, ASP.NET, and cloud-native architectures, ensuring 40% faster development cycles and fully optimized performance within the Microsoft ecosystem.
Azure data modernization updates existing data infrastructures using cloud-native services such as Fabric / Azure Data Factory for ETL, Microsoft Fabric Data Warehouse for data warehousing and big data processing, and Azure Databricks for collaborative analytics. Applications shift from on-premise servers to managed services that scale automatically and integrate with machine learning and AI toolkits.
This transformation lowers maintenance overhead and improves query performance through serverless compute and distributed storage. Organizations achieve cost reduction with pay-as-you-go billing models and automation of routine tasks. Enhanced data governance and built-in compliance controls help maintain security standards. Modernized environments support faster analytics experiments, real-time insights, and innovation in reporting and customer-facing applications.
Initiate the strategy with a technical assessment that maps data sources, evaluates latency requirements, and benchmarks throughput. Create data models that segment operational, analytical, and real-time streams. Use Fabric / Azure Data Factory for ETL orchestration and implement mapping data flows to handle schema drift.
Design a layered architecture: ingest raw data into OneLake / Azure Data Lake Storage Gen2, transform in Apache Spark on Azure Databricks, and serve datasets with dedicated SQL pools in Microsoft Fabric. Apply infrastructure as code through ARM templates or Terraform modules to provision storage accounts, Fabric workspaces, and Databricks clusters in a repeatable manner.
Implement governance and security controls using Microsoft Purview to catalog assets and integrate with Azure Role-Based Access Control. Define network isolation with virtual networks and private endpoints. Monitor pipeline health using Azure Monitor with custom Log Analytics queries and set alerts for data latency breaches.
Iterate on the strategy by collecting telemetry on job runtimes, cost per terabyte, and query performance. Tune Spark configurations, adjust scale-out settings in Synapse, and refine data partitioning. Update deployment scripts to reflect optimizations and maintain alignment with new Azure service capabilities.
Azure Migrate uses an agentless approach to discover servers and databases, capturing CPU, memory and disk I/O metrics. Analyze dependency maps to sequence migration waves and limit downtime. Use Azure Database Migration Service’s online replication mode to maintain transactional consistency during cutover.
Design the target environment around Microsoft Fabric dedicated SQL pools for high-concurrency analytics and OneLake / Azure Data Lake Storage Gen2 for raw and curated data zones. Define data flows in Fabric / Azure Data Factory with mapping Data Flow activities and scale out using integration runtime clusters. Configure virtual network peering and private endpoints to restrict traffic within the Azure backbone.
Tag resources to track environments and cost centers. Create Azure Monitor alerts on performance metrics and use Log Analytics queries for anomaly detection. Automate scaling rules on SQL pools based on query latency thresholds. Store encryption keys in Azure Key Vault and enforce access through role-based access control. Test failover scenarios with Azure Site Recovery for critical data pipelines.
Neglecting governance leads to data silos, security exposure, and compliance gaps. Unclassified data raises risk of unauthorized access and regulatory fines, while lack of lineage impedes issue resolution. Technical debt grows when uncontrolled datasets proliferate across storage accounts. Audits become time-consuming without centralized reporting.
Implementing policy-driven governance with Microsoft Purview and Azure Policy reduces exposure through automated classification and enforcement of access rules. This approach prevents data leaks and streamlines compliance reporting.
Organizations gain clearer asset visibility, faster incident response, and opportunities for self-service analytics. Standardized governance practices lower operational costs and support growth through reliable data foundations.
Modernizing data platforms on Azure reduces reporting delays and operating expenses. Consolidating information in a Data Lake cuts manual integration tasks, and Fabric shrinks report generation from days to hours. Marketing teams leverage that speed to send tailored promotions based on purchase history and browsing patterns, which lifts conversion rates.
Power BI dashboards supply product managers with interactive views of feature adoption and customer satisfaction. Those insights fuel prioritization of enhancements and alignment with strategic goals. Faster release cycles and data-driven segmentation boost upsell performance and support scalable revenue growth.
Consolidating legacy data systems into Azure’s platform lowers ongoing infrastructure spend by shifting from upfront hardware investments to pay-per-use services. Organizations observe improved cost transparency and the ability to adjust budgets as analytics workloads expand or contract.
Enhanced data accessibility across departments shortens the gap between data capture and decision-making. Executives rely on near real-time dashboards built on Microsoft Fabric's Data Warehouse and Power BI to monitor key metrics. This agility supports faster product iterations and more informed strategic planning.
Modernized data environments also reduce compliance liability through automated policies in Microsoft Purview. Teams spend less time on manual audits and more on innovation projects that drive revenue growth. Over multiple quarters, reduced time to insights and lower operational overhead translate into measurable ROI.
With over 25 years of technology experience in the financial services industry, Amit has spearheaded initiatives to modernize payments platforms, transform core banking systems, build new cash management platforms, launch embedded finance products, and leverage AI to reduce sanctions false positives.
I am a technology strategist and executive architect with over 20 years of experience designing, scaling, and modernizing digital platforms for startups, scale-ups, and enterprises.
My expertise lies in translating complex technology into business-aligned outcomes; driving innovation, resilience, and growth.
As Chief Architect, Fractional CTO, and founder of The Future Thinker, I help organizations navigate transformation through a blend of deep technical insight and forward-thinking strategy.
With over 14 Years of professional experience, I am passionate about enabling businesses to unlock value through transformative AI-driven solutions by aligning innovative data strategies with organizational goals.
Dedicated to fostering collaboration and delivering impactful results, I strive to bring diverse perspectives to every initiative while contributing to Virtusa's cutting-edge offerings in Europe.