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Data Warehouse Modernization in the Age of Big Data Analytics

Posted in: Business Intelligence - Apr 14, 2016

Data warehouses (DWs) and requirements for them continue to evolve. DWs are more relevant than ever, as they support operationalized analytics, and wring business value from machine data and other new forms of big data. Hence, it’s important to modernize a DW environment, to keep it competitive and aligned with business goals, in the new age of big data analytics. Yet, user organizations struggle to stay educated about trends and take the right action to modernize their DW investments. Many users need to catch up by deploying a number of upgrades and extensions to their existing DW environments and by adopting modern development methods. Once caught up, they need a strategy for continuous modernization.top

The Value of a Customer 360 Program

Posted in: Master Data Management - Apr 13, 2016

Getting to know more about your customers can strengthen and solidify your relationships with them.top

Business Intelligence Journal | Vol. 21, No. 1<br /><span class=’memberInlineSnipe’>TDWI Member Exclusive</span>

Posted in: Business Intelligence - Mar 11, 2016

If your enterprise isn’t always looking for better ways to do things, you won’t move or stay ahead. In this issue of the Business Intelligence Journal we look at companies and the moves they’re making, as well as moves you can make in your own environment.top

Business Intelligence Journal | Vol. 21 No. 1

Posted in: Business Intelligence - Mar 11, 2016

If your enterprise isn’t always looking for better ways to do things, you won’t move or stay ahead. In this issue of the Business Intelligence Journal we look at companies and the moves they’re making, as well as moves you can make in your own environment.top

Ten Mistakes to Avoid In Preparing for IoT Analytics<br /><span class=’memberInlineSnipe’>TDWI Member Exclusive</span>

Posted in: Business Intelligence - Mar 07, 2016

 

By Fern Halper and Asim Razvi

The Internet of Things (IoT)—a network of connected devices that can send and receive data over the Internet—is a hot market topic. Although many companies are excited about the possibility of improving operational efficiencies and driving new business models with IoT, this Ten Mistakes to Avoid identifies important factors to consider when getting ready for IoT analytics projects.

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