After all the ‘teasing’ in my previous post, let’s talk about what our Leap Data Transformation Framework actually is and how it works.
In a nutshell, Capgemini’s Leap Data Transformation Framework accelerates and industrialises the transformation of relational DW/BI landscapes into Big Data landscapes.
This is all possible thanks to:
- Proven methodologies that efficiently transform existing data from legacy DWs and data marts. Our methodology covers all the lifecycle phases of the transformation from estimation to data discovery and optimisation, and the design, realisation and testing of the transformation lifecycle;
- A set of modular tools, adaptable to a wide range of Big Data architectures and leveraging machine-learning techniques. These optimise and accelerate the data transformation and migration processes. We know the wide diversity of our clients’ data landscapes and this is why each of our framework modules can be easily adapted to suit our clients’ data needs;
- An automated approach providing greater speed, control, quality, efficiency and scalability;
- An agile deployment approach, based on continuous integration and DevOps, enabling rapid development and a fast transition into production.
Implementing our Leap Data Transformation Framework, and together in partnership with Cloudera, we have already helped some of our largest customers to achieve significant efficiencies in their transformation process to Big Data landscapes. These have already amounted to 30%+ savings for a large transformational process, here in the UK.
In the next post, I’ll outline how we’ve applied our Framework in practice and the results we’ve obtained. In the meanwhile, if you want to know more about Capgemini’s Leap Data Transformation Framework, follow this link