Databases Reference
In-Depth Information
FIGURE 10.9
Data virtualization-based Big Data integration.
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Operational costs—in this architecture the operational cost calculation has fixed and variable cost
components. The variable costs are related to processing and computing infrastructure and labor
costs. The fixed costs are related to maintenance of the data virtualization platform and its related
costs.
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Pitfalls to avoid:
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Loosely coupled data integration.
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Incorrect data granularity across the different systems.
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Poor metadata across the systems.
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Lack of data governance.
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Complex data integration involving too many computations at the integration layer.
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Poorly designed semantic architecture.
There are many more possible architectural deployments to integrate Big Data and create the next-
generation data warehouse platform. This chapter's goal is to provide you a starter kit to begin look-
ing at what it will take for any organization to implement the next-generation data warehouse. In the
next section we discuss the semantic framework approach.
Semantic framework
Building the next-generation data warehouse requires strong metadata architecture for data integra-
tion, but that does not solve the data exploration requirements. When data from multiple sources and
systems is integrated together, there are multiple layers of hierarchies including jagged and skewed
hierarchies, data granularity at different levels, and data quality issues especially with unstructured
