Data Warehousing services in USA

Technology Capabilities

Our Microsoft SQL engineers use this database management system for the primary function of storing and retrieving data as requested by other software applications—which may run either on the same computer or on another computer across a network.

Snowflake offers a cloud-based data storage and analytics service, generally termed “data-as-a-service”. It allows corporate users to store and analyze data using cloud-based hardware and software. It offers unified data across clouds to accelerate and scale analytics with near-zero administration.

This is a cloud-based data integration service that allows our engineers to create data-driven workflows in the cloud for orchestrating and automating data movement and data transformation. We shall not be able to store any data here since Azure Data Factory does not store any data itself.

Amazon Redshift uses SQL to analyze structured and semi-structured data across data warehouses, operational databases, and data lakes using AWS-designed hardware and machine learning to deliver the best price-performance at any scale.

Our Approach

Identify & Define Problem

Our team will analyze & identify the problem to propose solutions that conform to the needs and constraints of the problem

Develop a Proof of Concept

We create a Proof of concept that helps our clients to avoid possible technical setbacks and reduce unnecessary risks.

Assessment & Planning

Our data engineers will assess the entire project and be responsible for planning and scheduling project development.

Cross-team Collaboration

From the project discovery phase to delivery and beyond, our team always prioritize the cross-functional team collaboration for better productivity

Data Quality Engineering

Our quality engineers will automate data validation processes at different stages of development to meet business requirements & established quality metrics.

Project Delivery & Beyond

Our focus is not just to deliver a solution – but to partner with you throughout the journey and provide optimized business solutions

Success Stories

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Data Visualisation Platform for Enterprises
Online Hotel Reservation and Booking Platform
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Data Analysis for FinTech Industry
Analysis & Insights for Better Decision Making
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Data Automation for Marketplace Industry
Data Migration Strategy to Enhance Efficiency
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ML for Retail Demand Forecasting
Historical Data Analysis for Future Prediction

Our Award-Winning Team

A seasoned AI & ML team of young, dynamic and curious minds recognized with global awards for making significant impact on making human lives better

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50+

AI & ML
Engineers

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40+

AI & ML
Projects for
reputed Clients

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5yrs

in AI & ML
Engineering

Trusted and Proven Engagement Model

  • A nondisclosure agreement (NDA) is signed to not disclose any sensitive information revealed over the course of doing business together.
  • Our NDA-driven process is established to keep clients’ data and IP safe and secure.
  • The solution discovery phase is all about knowing your target audience, writing down requirements, and creating a full scope for the project.
  • This helps clarify the goals, and limitations, and deliver quality products & services.
  • Our engagement model defines the project size, project development plan, duration, concept, POC etc.
  • Based on these scenarios, clients may agree to a particular engagement model (Fixed Bid, T&M, Dedicated Team).
  • The SOW document shall list details on project requirements, project management tools, tech stacks, deliverables, milestones, timelines, team size, hourly/monthly rate cards, billable hours and invoice details.
  • On signing the SOW, an official project kick-off meeting shall be initiated.
  • Our implementation approach, ecosystem, tools, solutions modelling, sprint plan, etc. shall be discussed during this meeting.
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