TDWI Checklist: Using Hadoop for Data Warehouse Optimization
January 1, 2018
You have a legacy system that no longer meets the demands of your current data needs, and replacing it isn’t an option. But don’t panic: Modernizing your traditional enterprise data warehouse is easier than you may think.
Traditional data warehouses are built on a costly model: with lengthy deployment cycles, time to value can delay your enterprise data warehouse’s time to value. But there is a way around this— by leveraging the power of Hadoop and open source technologies like Hive, you can exploit pools of commodity computing and storage resources, allowing your system performance to scale proportionally to demand while reducing overall costs.
Read the TDWI Checklist Report on Using Hadoop for Data Warehouse Optimization and learn how to:
- Leverage Horizontal Scalability/Elasticity with Open Source Technologies to Reduce Costs
- Augment enterprise data warehouse storage with Hadoop and Hive
- Use Flexible Data Organization to Enable Schema on Read