Modern analytics depends on more than storage — it requires a data platform that is governed, scalable, and designed to support real business questions.
Our Data Platform Services help organizations design, build, and operate data foundations that turn fragmented data into trusted, analytics-ready assets.
We combine proven architectures, automation, and governance best practices to accelerate delivery while keeping platforms secure, performant, and future-ready.

Data Platform Services

Lakehouse-in-a-box

Unified Data Architecture

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Data Integration & Automation

Seamless Pipelines

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Data Virtualization

One Data View

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Data platform Management

Secure & Scalable Ops

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SOLUTION OFFERINGS

Lakehouse-in-a-box

deploy a modern data foundation—fast, scalable, and analytics-ready

We deliver a pre-configured lakehouse platform that combines the flexibility of a data lake with the structure and performance of a data warehouse. Designed for rapid deployment, Lakehouse-in-a-Box removes the complexity of building a data platform from scratch while preserving the ability to scale and evolve over time.

This approach is ideal for organizations that need speed without sacrificing governance, whether for a new analytics initiative, cloud migration, or modernization of legacy data warehouses.

Support structured, semi-structured, and unstructured data within a single Lakehouse architecture

Enable batch-based analytics and historical reporting across multiple data domains

Reduce data duplication by consolidating analytics workloads on a common platform

Unified Architecture

Pre-Built Deployment

Delivered as a pre-configured reference architecture to reduce design and setup effort

Supports deployment on AWS, Microsoft Azure, and on-premises environments

Accelerates platform implementation timelines compared to fully custom builds

Analytics & AI Ready

Designed to support business intelligence, advanced analytics, and data science workloads

Enables SQL-based analytics and integration with machine learning and analytics frameworks

Compatible with lakehouse and analytics technologies such as Databricks Delta Lake, Apache Spark, and Snowflake

Architecture designed to scale with data volume and analytical workload growth

Supports separation of storage and compute to improve resource efficiency

Enables consumption-based cost models when deployed on cloud platforms

Scalable & Cost-Optimized

KEY BENEFITS

by integrating data across critical business systems and platforms.

Faster time-to-insight

by consolidating analytics workloads and reducing unnecessary data duplication.

Lower TCO (Total Cost of Ownership)

through simplified platform architecture and reduced reliance on multiple parallel data platforms.

Future-proof architecture

Designed to support evolving analytics and machine learning use cases as business needs grow.

Improved governance and compliance

With centralized data management, control, and auditability built into the platform design.

SOLUTION OFFERINGS

Data Integration and Automation

Designing and operating reliable data pipelines across on-premises and cloud environments.

Modern enterprises operate across multiple applications, systems, and data platforms. Without effective integration, data remains fragmented and difficult to use consistently.

Our Data Integration & Automation services focus on designing, building, and operating data pipelines that reliably move and transform data across on-premises, cloud, and hybrid environments, supporting analytics, reporting, and downstream data consumption.

Seamless Connectivity

Leverage connectors provided by leading integration tools to connect cloud, on-premises, and hybrid data sources

Support structured, semi-structured, and unstructured data ingestion

Enable integration between legacy systems and modern cloud-native platforms

Automated Pipeline

ETL and ELT pipelines designed to support batch and near-real-time data processing where required

Data ingestion pipelines supporting scheduled and event-driven workloads

Automated transformations to cleanse, standardize, and enrich data before downstream consumption

Workflow

Resilience

Continuous monitoring of integration pipelines to detect errors early

Configurable retry, rerun, and recovery mechanisms within integration workflows

Reduced downtime and minimized manual intervention

Faster Time-to-Insight

Timely delivery of data to analytics, dashboards, and downstream platforms

Data delivered in standardized, business-ready formats for consumption

Enable advanced analytics and data science teams by providing reliable, well-prepared data

KEY BENEFITS

Reducing data fragmentation and improving operational efficiency

Reduce data silos

by integrating data across critical business systems and platforms.

Improve operational efficiency

by automating repetitive data integration and transformation processes

Enable analytics and advanced use cases

by delivering curated and timely data to analytics and data science platforms.

Enhance platform agility

by enabling flexible data pipelines that adapt to changing business and regulatory requirements.

SOLUTION OFFERINGS

Data Virtualization

Access data across multiple sources with minimal duplication

In today’s multi-cloud and hybrid environments, data is scattered across systems, applications, and storage layers. Moving and copying this data creates silos, drives up costs, and introduces governance risks. Data Virtualization addresses this by providing a single, logical access layer that allows teams to query, analyze, and use data across multiple sources without physically relocating the data. This reduces architectural complexity, lowers infrastructure and replication costs, and accelerates access to data for analytics and reporting.

Unified Data Access

Seamlessly connect to databases, cloud storage, SaaS applications, APIs, and on-premise systems.

Create a single point of access for analysts, data scientists, and business users.

Reduce reliance on IT-heavy integrations and empower self-service data discovery.

Real-Time Insights

Query data directly from live sources, ensuring decisions are made on the most current information.

Enable dashboards, reporting, and advanced analytics without waiting for batch ETL loads.

Support mixed workloads — operational reporting, ad hoc queries, and AI/ML applications.

Cost Efficiency

Eliminate the need for multiple storage environments and redundant copies of data.

Reduce infrastructure overhead by querying in place rather than replicating data.

Streamline compliance and data retention by minimizing data sprawl.

Secure & Governed Access

Role-based permissions ensure that users see only what they’re authorized to access.

Centralized governance framework to enforce policies across all data sources.

Audit and compliance-ready logging to meet industry regulations.

KEY BENEFITS

One virtual layer. All your data. Zero duplication.

Lower costs

by eliminating redundant data movement and storage.

Accelerate insights

with real-time analytics on live data.

Improve governance

through centralized access and compliance controls.

Boost agility

by enabling new use cases quickly without re-architecting pipelines.

SOLUTION OFFERINGS

Data Platform Management

Keep your data infrastructure reliable, secure, and future-ready.

Data Platform Management ensures that your data environment — whether on-premise, cloud, or hybrid — operates at peak performance while evolving with your organization’s needs. It encompasses strategic planning, platform creation, and continuous optimization to maintain a robust and scalable foundation for all your data initiatives.