Innovating with Best Practices to Modernise Delivery Architecture and Governance

2019-10-24T04:48:00+00:00Categories: AI Engineering Curriculum Electives, Data Science Level 2, Data Science Curriculum Electives, Executive Curriculum Electives, Data Governance Curriculum, Innovation & Tech (CTO) Level 2, Stephen Brobst, Data Engineering Curriculum, Data Governance Level 1, Data Management, Innovation & Tech (CTO) Curriculum, Executive Level 2, Infrastructure & Technologies, Big Data, Data Engineering Level 1, AI Engineering Level 2, All Academy Courses|Tags: , , , , , |

Organisations often struggle with the conflicting goals of both delivering production reporting with high reliability while at the same time creating new value propositions from their data assets. Gartner has observed that organizations that focus only on mode one (predictable) deployment of analytics in the construction of reliable, stable, and high-performance capabilities will very often lag the marketplace in delivering competitive insights because the domain is moving too fast for traditional SDLC methodologies. Explorative analytics requires a very different model for identifying analytic opportunities, managing teams, and deploying into production. Rapid progress in the areas of machine learning and artificial intelligence exacerbates the need for bi-modal deployment of analytics. In this workshop we will describe best practices in both architecture and governance necessary to modernise an enterprise to enable participation in the digital economy.