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TDWI Checklist Report | Data Warehousing in the Cloud

June 29, 2015

An impact of the burgeoning business interest in analytics is increased interest among small and midsize businesses to adopt a business intelligence (BI), reporting, and analytics strategy. In the past, larger organizations may have been willing to invest in hardware, software, and expertise to establish an enterprise data warehouse environment. However, smaller businesses have often lacked the budget, access to skilled professionals, or the determination to design, build, and support the necessary dedicated platforms.

Expanding the pool of organizations able to embrace a data warehousing and BI capability depends on:

  • Reducing the complexity of instantiating an analytics environment
  • Lowering the cost barrier to entry
  • Unshackling business users from the information technology (IT) department by providing rapid accessibility to data using self-service analytics tools

Fortunately, as data professionals have gained experience in implementing common design patterns and integration models, the data warehousing industry has matured, resulting in a general agreement about the architecture of an end-to-end BI and analytics framework.

Coupling this prototypical architecture with increasingly sophisticated software tools addresses this challenge. It simplifies launching a dedicated system for data analysis and reduces the need for specialized skills. The convergence of the standardized architecture for data warehousing and BI, advances in data integration and data discovery technologies, and cost models of utility computing via the cloud enables vendors to develop cloud-based data warehousing systems.

This paradigm allows vendors to instantiate their tool suite as a managed platform in a way that presents a special opportunity for a broad community of businesses to fulfill the objectives of their analytics strategies. Relying on a service provider to instantiate the platform simplifies the business’s progression toward the advantages of analytics. Using a cloud-based data warehouse eliminates the need for capital hardware investments and IT support staff to configure and manage the platform. This frees the data scientists, analysts, and architects to focus on the analytical models that will improve business performance.

Our objective in this Checklist Report is to share best practices that will position the reader to take advantage of a cloud-based data warehousing solution.

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