Level: Beginner to Intermediate
Building a data warehouse has always been an essential enterprise project, one that is theoretically well understood but in practice has left enterprises in a state of disarray. In recent years, there has been a tremendous increase in infrastructure and platform innovation. Many of these evolved platforms, when interconnected, can deliver on the enterprise mission of a modern data warehouse.
At the same time, predictive analytics and machine learning (PAML) is on the agenda of every organization across the globe. PAML has made it to the boardroom and is deemed central to business strategy and transformation. The transition of analytics from end-user computing to an enterprise capability generates new pressure for governance and support—both from IT and from the business. How do you avoid a culture clash between analysts and IT which has previously led to six iterations of “AI winters?” How can you enable capabilities such as edge analytics and interactive visualizations?
Enterprise architects must provide a clear conceptual framework for a modern data warehouse and the analytical capabilities it will support. The challenges are many; enterprise analytics often requires 99.999% availability, safeguards against breaches and breakdowns, and support for heterogeneous platforms. Above and beyond this, the platform must be able to accommodate every type of user and their requests, whether data set or analytics or interactive visualization.
Attend this session to learn all about modern data platforms, advanced infrastructures, and architecture of the modern data warehouse.
You Will Learn
- The foundational requirements of modern data warehouse and analytics solutions
- Business value delivery (operational to prescriptive analytics)
- Pitfalls, risks, and mitigation strategies of modern data platforms for data and analytics
- How to tap into the cloud data center
- How to orchestrate workloads and workflow for scalable environments
- Architectural frameworks and system interfaces for taming complexity
- Enterprise architects
- System API designers
- Full stack engineers
- Product managers
- UI/UX practitioners