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No matter the vintage or sophistication of your organization’s data warehouse (DW) and the environment around it, it probably needs to be modernized. DW modernization takes many forms. Common scenarios range from software and hardware server upgrades to the periodic addition of new data subjects, sources, tables, and dimensions. As data types and data velocities continue to diversify, many users are likewise diversifying their software portfolios to include tools and data platforms built for new and big data. A few organizations are even decommissioning current DW platforms to replace them with modern ones optimized for today’s requirements in big data, analytics, real time, and cost control. No matter what modernization strategy is in play, all require significant adjustments to the logical and systems architectures of the extended data warehouse environment.

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