The Lambda Architecture delivers the promise of analytics that is both real-time over streamed data and batch over comprehensive data. But its use relies largely on individuals with architecture savvy and sys admin skills for the capture, scheduling, and deployment of analytical models
We introduce a Model Management Framework that presents a simplified interface that supports end-to-end analytical modeling at scale using the Lambda Architecture. The framework hides the complexity of Lambda and unlocks its power for data scientists, domain experts, and business analysts. - Data scientists and domain experts who generate the models can select from already captured modeling approaches or onboard their own. The platform makes it easy to compare models in a champion-challenger fashion. - Business analysts who rely on model’s results can select from a catalog of models created by experts. Model Management Framework comprises of a model building service, a prediction service, and a resource allocation service. The result enables a catalog approach to finding analytics, simplified onboarding of new analytics, and a brute-force approach to retraining and comparing models.
How to apply and next steps Identify desired insights Data collection Model-driven analytics Take