Latest News
1) iBilt has been awarded the project from Delhi Govt., India, for Integration and Content Management Services for 97 websites into a single portal.

2) iBilt's CMMi V1.2 assessment for Maturity Level 5 has been approved and accepted by the Software Engineering Institute (SEI). The assessment for the same was conducted from December 3 to December 13
in the year 2007.
Service Portfolio >>Data warehousing and business intelligence (DW/BI)
Data is the source of all decisions and iBilt assists its clients use data for effective decision making. By implementing state of the art data warehouses and business intelligence tools, iBilt ensures that decision-making is more effective for its clients. We provide consulting services leading to successful implementation of the Data Warehouse. This may involve the following components of our services:

Management Consulting
  • Business operations strategies and Data Warehouse strategy alignment
  • Data warehouse Strategy
  • Aligning Business goals and Business Intelligence objectives
  • Determining Information Requirements 
  • Identify and specify applications Architectural Design
  • Hardware and software sizing and specifications
  • Skill Requirements
  • Implementation Phases and Strategies
  • Training Requirements & Schedules

Functional Consulting

  • Conceptual Data Modeling 
  • Logical Data Modeling 
  • Physical Data Modeling
  • User Interface
  • Security and Network Management
  • Development and Testing Phases
  • Development & Deployment Services
  • Project Management 
  • Systems and Application Development
  • Systems Integration Services
  • Operational Support Services
  • Documentation
  • Maintenance Services
  • Design Reviews
  • Education and Training

IBilt works with clients throughout Analysis, Design, Construction and Test & Implementation phases and transfer skills during each phase of the project.

We provide solutions for robust open systems that are scaleable, manageable, extensible, flexible, integrated, accessible, available and reliable without dependency on specific tool or technology.

We have worked out critical success factors for each task performed in a data warehouse project. We apply these critical success factors for the entire project and also specific critical success factors relevant to each project stage enhancing quality and relevance.