Data Warehouse Modernization In the Age of Big Data Analytics

Description: No matter the vintage or sophistication of your organization’s data arehouse (DW) and the environment around it, it probably needs to be modernized in one or more ways. That’s because DWs and requirements for them continue to evolve. Many users need to get caught up by realigning the DW environment with new business requirements and technology challenges. Once caught up, they need a strategy for continuous modernization. DW modernization assumes many forms, from server upgrades and tweaks for data models, to adding new platforms into the extended data warehouse environment (DWE), to replacing the primary DW platform. Modernization may involve using features previously untapped, such as inmemory databases, in-database analytics, real-time functions, and data federation or virtualization. Systems integrated with the DW need attention, too. Analytics, reporting, and data integration are also modernizing, and the DW is under pressure to provision data in ways that enable modern endu