For many organizations, the current approach for delivering reporting to the business is siloed and there is a struggle to bring data together, resulting in data duplication, inconsistent business logic, and a reliance on manual processes making it difficult to maintain and get accurate insights for decision making.
Siloed business solutions and copies of data with inconsistencies that cause considerable time and effort to find data and reconcile.
Manual/redundant activity working with Excel spreadsheets with limited capabilities to track and analyze high impact analytical use case to make informed business decisions.
Lack of scalability and performance, outdated technology, and increasing costs of maintenance and support highlight the importance of assessing and modernizing aging infrastructure. The further behind business lag the more painful these challenges become.
We partner with clients and use our proven cloud migration approach to justify cloud investments, deploy technical foundations, and manage the migration roadmap.
Our BI Cloud Migration approach will help drive alignment on future vision and architecture, identify data needs, assess current capabilities, and chose a modern data warehouse platform.
Determine cloud and data goals, benefits, risks and constraints. Conduct future-state visioning interviews for data analytics requirements that are aligned to business objectives.
Clear, agreement on vision for cloud-based data-enabled processes, analytics and capabilities.
Review existing technology landscape.
Understanding of current data environment (data, processes, organization).
Analyze pain points and gaps to inform future-state Architecture Select technology & tools.
Agreement on modern data warehouse platform, automation, and tools for DW.
Develop future state Conceptual Architecture.
Define & scope implementatyion plan with eeffort, resources and cost.
Create Proof-of-Concept for Reporting/Visualization.
Roadmap of actions and recommendations for implementation and ongoing support.
Increase utilization of data by making data available and accessible where and when business users need it.
Innovate on new business opportunities through a flexible and scalable data infrastructure.
Robust data integration framework to quickly and consistently validate data and handle potential data errors.
Reducing data-related efforts through tool modernization and increased automation.