Using Hadoop to Lower the Cost of Data Warehousing: The Paradigm Shift Underway
Data warehouses are bursting from increased data volume, and new sources of data are making traditional approaches to data analysis costly and slow. Typically, analysts define the problem, identify data samples and pull the data through an ETL (extract, transform and load) process. But now, Hadoop is changing the data-warehousing landscape by improving data archiving and lowering costs by offloading data warehouse processing. A Hadoop platform enables companies to easily scale as the volume, velocity and variety of data continues to increase while providing even higher-quality results.
This class will cover the operational cost of deploying Hadoop relative to more traditional data-warehousing implementations. We will cover real-world customer use cases and demonstrate how dramatic cost savings (often a magnitude of savings) were achieved through properly deployed Hadoop implementations.
Level : Overview