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Data Warehouse Moderization


What is the Data Warehouse Moderization big data use case?

Data Warehouse Moderization (formerly known as 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 Moderization:


Ask yourself:

checkmark Are you integrating big data and data warehouse capabilities to increase operational efficiency?

checkmark Have you taken steps to migrate rarely used data to new technologies like Hadoop to optimize storage, maintenance and licensing costs?

checkmark Are you using stream computing to filter and reduce storage costs?

checkmark Are you leveraging structured, unstructured, and streaming data sources required for deep analysis?

checkmark 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 Moderization use case is the best starting point for your big data journey.

With Data Warehouse Moderization, organizations can:

Big Data Use Case - Data Warehouse Augmentation

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    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

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    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)


Case Study

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    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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