Data Platform Services

Our Data Platform Services

Consulting Services for Enterprise Data Strategy, Data Engineering Strategy, Data Operations Strategy in both cloud and on-premise platforms with a focus on improving collaboration, automation and efficiency in data product development lifecycle. As part of aforementioned data strategy across the pillars, we specialize in providing DataOPS solutions by following the process guidelines outlined in DEVOPS and SRE (Site reliability engineering).

Elements of a Data Platform

Data platforms include data storage, servers and data architecture. Beyond that, there's data ingestion needs, data consolidation and the ETL process.

Businesses regularly face challenges with data management, including the unification of disparate data types housed in various silos, data lakes and on-premise servers.


The goal of a data platform is to deliver real-time business insights through analytics in a cost-efficient, scalable and secure manner. Today's most efficient platforms can housed across disparate geographies and in cross-cloud (or multi-cloud) environments to meet unique local or line-of-business requirements and to strengthen business continuity plans.

Businesses seek a system provides a one-stop destination. A key element of that outcome entails unifying diverse data, including structured and semi-structured data.

Modern data platforms enable customization (through data engineering and development) along with easy integration to BI tools and analytics applications. They can also facilitate training of machine learning models.

We specialize in:
  • Domain specialization in Healthcare (Insurance, Drugs, Provider & Patient) and BFSI
  • Data Lake and Data Lakehouse solutions
  • Cloud Data Analytics solutions
  • Data Ingestion Services with a focus on Business continuity
  • Data Operations
Our Data Engineering team is comprised of:
  • Junior Data engineer
  • Senior Data Engineer
  • Data Solutions Architect
  • Domain Experts
How do we upskill?

Our skilled data engineers are encouraged to participate in periodic Community of Practice trainings held at the organization to discuss, learn and gain insights into evolving data ingestion patterns, data processing, data consumption and data virtualization patterns.