Developing a data architecture used to be straightforward, but lowered expenses and simplified management are inspiring senior managers to migrate many enterprise reporting and analytics infrastructures to the cloud.
Cloud service providers are rapidly producing a dizzying array of storage, computing, and other value-added services. Old fashioned extract, transform, and load (ETL) processes are being supplanted by data onboarding and pipeline orchestration. As multicloud hybrid architectures get more complicated, even highly technically trained people have trouble keeping track of what’s what.
Organizations increasingly need to support more sophisticated data scientists as well as a broader community of citizen data analysts. Both need to be enabled without creating additional IT bottlenecks.
This TDWI Checklist is intended to increase awareness about cloud data warehouse architectural paradigms. Here we will provide some straight talk about the current state of data warehousing and discuss emerging platform paradigms that complement the traditional data warehouse and how these components can be deployed across a hybrid cloud architecture.
Sponsored by Matillion
Individual, Student, and Team memberships available.