Data & Analytics - From noise to enterprise asset
Challenges with data is the topmost reason for failure of AI strategy. Your data differentiates you from your competitors. Convert raw data into wisdom and actionable insight - consult with us.
Challenges with data is the topmost reason for failure of AI strategy. Your data differentiates you from your competitors. Convert raw data into wisdom and actionable insight - consult with us.
Partner with business and technology leaders to develop a pragmatic data strategy that aligns with corporate goals. We define target architectures, roadmaps, use-case prioritization, KPIs and a data product operating model to unlock measurable business outcomes.
Evaluate your current data estate, people, processes and tools to identify gaps and quick wins. Our assessment produces an actionable remediation plan covering data quality, lineage, security, storage and engineering effort estimations for prioritized initiatives.
Design and implement resilient lakehouse, mesh or fabric-based architectures that scale for analytics and AI. We select the right architecture patterns, cloud services and integration approaches to balance performance, cost and operational simplicity.
Build robust, production-grade pipelines for batch and streaming workloads using modern ETL/ELT, orchestration, and transformation tooling. Our teams implement scalable ingestion, transformation, cataloging and delivery patterns with observability built-in.
Implement lifecycle, cataloging, metadata management and storage strategies to make data discoverable and reusable. We provide data catalog, retention and storage optimization approaches to reduce costs and accelerate analytics and ML adoption.
Establish guardrails for data access, stewardship, policy enforcement and regulatory compliance. Our governance frameworks balance control with agility so teams can innovate while ensuring privacy, security and auditability.
Define measurement metrics and automated checks to improve trust in analytical and ML datasets. We implement monitoring, remediation workflows and lineage tracing so stakeholders can quickly understand data origins and confidence levels.
Turn insights into action with interactive dashboards and self-serve analytics built around your users. We design performant, role-based visualizations and reporting layers that surface high-value metrics and enable data-driven decisions.
Introduce DevOps principles into your data lifecycle — CI/CD for pipelines, automated testing, and end-to-end observability. This reduces incidents, accelerates delivery and keeps production data reliable for analytics and ML models.
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Design and implement scalable data warehousing solutions using Amazon RedShift, Data Lake architectures on S3, and end-to-end pipelines using AWS Glue.
Implement comprehensive data solutions using Azure SQL, Cosmos DB, and Microsoft Fabric for unified analytics and AI-powered insights.
Leverage Google Vertex AI and BigQuery for advanced data analytics, MLOps workflows, and scalable AI infrastructure solutions.
Design cloud-native data platforms using Snowflake for seamless data sharing, warehousing, and unified analytics across multi-cloud environments.
Build lakehouse architectures using Databricks for unified data engineering, Spark-based processing, and scalable data pipelines.
Expertise in efficient database solutions including PostgreSQL, SQL Server, MongoDB, Cassandra, and DynamoDB for diverse use cases.
Client: UK-based Automobile and Home Insurer. 500,000 quotes a day, 4 million customers
Scope: Migration of Guidewire, Apps (100+), APIs, Microservices, Data, Infra and DevOps to Azure.
Europe's first successful modernization and migration of Guidewire to cloud (> 15 mil GBP)
Tech stack: Azure, Azure VMware Solution (AVS), APIM, Snowflake, Azure Data & Integration, Guidewire
Outcome: Increased performance by 1.6 times. 4 to 5 times faster insurance adjustments. Legacy-free IT estate, APIfication, automation, data modernization, and operational cost savings.
Client: Asia based health insurance and financial services major
Scope: Modernization and cloud migration of legacy and complex apps to Azure.
Apps: 20+
Lines of code: 2 million +
Technology: Azure, Java, .NET, Sybase, SQL Server, DB2, WebSphere MQ
Client: Middle east based petroleum and natural gas major
Scope: Define strategy & platform architecture for a new Joint venture organization that would be curved out from parent company
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