Get in touch
Connect with our experts to understand how Ippon Australia can assist you ground your decision in qualitative research that actually changes minds.
Conor Silke
Business Development Manager
csilke@ippon.tech
Raja Jani
Chief Data Officer
rjani@ippon.tech
Speed to value through DataCloud Launch™
Many data analytics implementations drag on for 6-9 months or more, racking up unnecessary costs while waiting for the big reveal.
With Ippon, enjoy clear deliverables, transparent pricing, and go-live in less time than most Data partners take to just plan and scope.
Ditch the bloated projects. Launch on time and on budget with our 10 week DataCloud Launch service for just $140k - half the cost with our methodology.
Best practice & project collaboration
Training & knowledge transfer
Guaranteed launch & add capabilities sooner
Post-project support & 90 day guarantee
10 Week Timeline
Week 1 to 2: Assessment & Planning
- Assess the current data infrastructure and identify data sources
- Define the scope of the implementation and identify data sources
- Develop a project plan with milestones, timelines, and resource allocation
Week 3 to 4: Data Ingestion & Integration
- Set up environment and configure security settings
- Create a data ingestion strategy using best practices
- Integrate data sources and load data into data warehouse/lakehouse
- Validate data quality and consistency
Week 5 to 6: Data Transformation & Optimisation
- Implement data transformation processes using ELT (Extract, Load, and Transform) method
- Optimise data storage and compute resources to minimise costs
- Apply data governance and access controls
- Monitor and fine-tune performance
Week 7 to 8: Data Analytics & Reporting
- Develop data models and analytics workflows
- Create custom reports and dashboards for various business units
- Implement real-time data analytics for improved decision-making
- Train end-users on how to access and use analytics tools
Week 9 to 10: Deployment & Support
- Deploy solution to production environment
- Monitor system performance and address any issues
- Provide ongoing support and training for end-users
- Evaluate the success of the implementation and identify areas for improvement
