Cloud migration as part of a data modernization strategy affords the opportunity to rethink how business partners consume data from a holistic and systemic perspective. Organizations are exploring alternative data architectures such as cloud-based data warehouses, data lakes, data lakehouses, and data mesh to support downstream data consumption. At the same time, the ability to use a broader array of data sources originating inside and outside the business’s administrative domain creates pressure for ingesting, processing, and integrating data across cloud, SaaS, and on-premises platforms.
Growing data volumes and increasing data demands require more sophisticated methods for data integration in the cloud. In this talk, we discuss how three key motivators have influenced the evolution of data integration in the cloud, namely DataOps practices, conceptual semantic data layers, and consumer data enablement.
David Loshin will discuss:
- Data lakes and data lakehouses
- Unified data platform for the cloud
- Data pipeline orchestration