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TDWI Checklist Report: Where Hadoop Fits in Your Data Warehouse Architecture

TDWI Checklist Report | Where Hadoop Fits in Your Data Warehouse Architecture

July 22, 2013

Business intelligence (BI) and data warehousing (DW) professionals are aware of Hadoop’s general benefits for BI and DW. They even know that Hadoop’s most credible use cases focus on analytics and managing multi-structured and no-schema data. This is good news for the integration of Hadoop into mainstream BI and DW practices. However, the Hadoop ecosystem of products is still quite new, so most BI and DW professionals haven’t yet determined where to begin their integration of Hadoop with established platforms for BI, DW, data integration (DI), and analytics.

The first step toward successful integration is to determine where Hadoop fits in your data warehouse architecture. Hadoop is a family of products, each with multiple capabilities, so there are multiple areas in data warehouse architectures where Hadoop products can contribute. At the moment, Hadoop seems most compelling as a data platform for capturing and storing big data within an extended DW environment, plus processing that data for analytic purposes on other platforms.

This TDWI Checklist Report discusses adjustments to DW architectures that real-world organizations are making today, so that Hadoop can help the DW environment satisfy new business requirements for big data management and big data analytics.

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