Читать книгу Smarter Data Science - Cole Stryker - Страница 17

Illustrated in Figure 1-1, the level of analytics sophistication accessible to the organization increases with each rung. This sophistication can lead to a thriving data management practice that benefits from machine learning and the momentum of AI.

Organizations that possess large amounts of data will, at some point, need to explore a multicloud deployment. They'll need to consider three technology-based areas as they move up the ladder.

 Hybrid data management for the core of their machine learning

 Governance and integration to provide security and seamless user access within a secured user profile

 Data science and AI to support self-service and full-service user environments for both advanced and traditional analytics

Figure 1-1: The AI Ladder to achieve a full complement of data and analytics

These foundational technologies must embrace modern cloud and microservice infrastructures to create pathways for the organization to move forward and upward with agility and speed. These technologies must be implemented at various rungs, enabling the movement of data and delivering predictive power from machine learning models in various types of deployment, from a single environment to a multicloud environment.