Data Warehouse Augmentation
What is the Data Warehouse Augmentation big data use case?
Data Warehouse Augmentation is about building on an existing data warehouse infrastructure, leveraging big data technologies to ‘augment’ its capabilities. There are three key types of Data Warehouse Augmentation:
Are you integrating big data and data warehouse capabilities to increase operational efficiency?
Have you taken steps to migrate rarely used data to new technologies like Hadoop to optimize storage, maintenance and licensing costs?
Are you leveraging structured, unstructured, and streaming data sources required for deep analysis?
Do you have a lot of cold, or low-touch data that is driving up costs or slowing performance?
If you answered yes to any of the above questions, the Data Warehouse Augmentation use case is the best starting point for your big data journey.
With Data Warehouse Augmentation, organizations can:
Big Data Use Case - Data Warehouse Augmentation
Watch as Vijay Ramaiah, Product Manager IBM Big Data, shows how the new big data technologies can provide valuable new capabilities that extend and augment your existing Data Warehouse to deliver broader analytics, more value and improved ROI.
Extending the Value of Your Data Warehouse: Big Data Use Case
Christy Maver, IBM big data product marketing manager, explains how data warehouse augmentation can help lower costs, provide the ability to perform analysis on more and new types of data. Listen to the podcast (MP3, 00:14:35, 6,7MB)
Learn how Constant Contact improved analysis performance by over 40 times, reduced wait time from hours to seconds, and increased client campaign effectiveness by almost 25%
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