Integrating with Data Lakes, Cloud, and Self-Service
Though pundits have declared the data warehouse dead, most organizations continue to operate at least one data warehouse, with the majority operating two to five, and expect to do so for the foreseeable future. New types of data drive new types of analytics needed to drive better and deeper business insight, and the data warehouse is core to these new use cases.
Data warehousing is alive, but perhaps not alive and well.
Current data warehouse infrastructures must be modernized to fit gracefully into new analytics ecosystems, evolving both architecturally and technologically. Yet in many instances, data warehouse evolution is stalled due to uncertainty about what, how, and when to change.
Get guidance from this Eckerson Group report.
Learn how to begin modernizing to data warehouses that are affordably agile, scalable, and adaptable in the face of continuous change. See how patterns of architectural restructuring, cloud migration, virtualization, and more can be used to combine data warehouses with big data, cloud, machine learning and other recent technologies to resolve many of today’s business analytics challenges and to prepare for the future of data warehousing.