As a Data Scientist, you develop models using a diverse selection of interfaces, algorithms, and tools. Similarly, IT leaders adopt a variety of different environments and paradigms in which to execute analytics—on-premise, in the cloud, hybrid, via APIs, real-time, in-database, on server, on the edge, the list goes on!
A challenge for many organizations is to manage this Analytical Heterogeneity with ongoing governance, orchestration, traceability, scalability, monitoring, and the ability to leverage any available technology.
This interactive eBook, Mastering Model Lifecycle Orchestration, will enable you to quickly identify where you sit in the Model Lifecycle journey and to get practical guidance on tackling and overcoming your challenges. The aim is to provide you with an answer to the question, “I trained my models. Now what?”