I-BiDaas

Participants
Start Year / End Year
Scope
Funding Framework
Budget
Duration
I-BiDaaS
Key Objectives
1. Industrial Challenges
2. State Analysis
3. Technical Architecture
4. Experimental Validation
5. Rapid Analytics
6. Real Validation
I-BiDaaS Project Focus
Self-Service Analytics
Make big-data analytics accessible to non-experts through an intuitive, self-service platform.
Data Integration
Break intra- and inter-sector data silos to enable unified, cross-domain data flows.
Secure Processing
Provide a safe environment for experimentation using sensitive, real-world industrial data.
Scalable Analytics
Increase speed and scalability of data analysis to match rapidly growing datasets.
Real-World Pilots
Validate the platform through industry-led pilots in banking, manufacturing and telecommunications.
Visualisation Tools
Develop interactive visual tools that support decision-making for users at all levels.
Synthetic Data
Create realistic synthetic datasets when real data is unavailable or sensitive, aiding experimentation.
Resource Optimisation
Improve management of computational and storage resources for efficient analytics operations.
Role of EPBS in I-BiDaaS









