Transforming Data Warehouse and analytics to the cloud is a complex task and can go wrong without careful planning.
Key challenges faced by organizations in their Journey to the Cloud:
Architectural blueprint is defined in the Journey to the Cloud phase, we do this by selecting the right tools available in a cloud stack that optimize Total Cost of Ownership (TCO), enable real-time capabilities, bring in self-service and minimize efforts.
Once best fit cloud services are put together as a blueprint, then task of cloud transformation begins with a chosen use case.
An incremental approach vis-à-vis a big bang approach will help to feedback the environment specific learnings into the transformation program without any risks or disruption to the business.
Our incremental approach involves using a Minimum Viable Product (MVP) as an important cloud adoption strategy. This acts as the right starting point as it validates the transformation approach and ensures that all specific customizations for maximizing automation are identified and implemented. Post this validation, Amaze™ for Data & AI gets customized to the environment to accelerate the rest of the transformation efforts.
With the learnings and insights from the MVP, a full-fledged transformation of the Data Warehouse, BI and analytics systems will be setup to run in a factory model.
The entire ETL code conversion, database schema transformation, data and reports movement are automated, which reduces time, efforts and cost involved by over 60%.
Through Amaze™ you can automate the transformation from:
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