RESEARCH & RESOURCES

TDWI White Paper Library

TDWI maintains this library of white papers as a resource for in-depth research and commentary about the big data, business intelligence, data warehousing, and analytics industry. The content in this repository is crafted by TDWI's software and consulting partners. To find out how your company can promote its content in this library, click here.


Top BI Trends 2019: The Dawn of Postmodern Analytics

January 1, 2019

Data is at a crossroads. Massive corporations are consolidating our data while many of us advocate for transparency and access for all. It’s time to embrace postmodern analytics for even better performance, deeper insights, and broader participation.


IBM white paper

Technical Validation: Hybrid Multi-cloud Artificial Intelligence: IBM Watson Studio and Watson Machine Learning

January 1, 2019

ESG recently completed testing of IBM Watson Studio and Watson Machine Learning, which are designed to enable organizations to accelerate the value they can extract from AI more easily.


Fueling Digital Transformation with Data: Four Approaches that Get You There Faster

January 1, 2019

If you want to compete in the digital world, you have to find ways to reinvent every aspect of your business. To do that, you need an analytics strategy that gives everyone in your workforce the power to make game-changing discoveries.


IBM white paper

A Business Guide to Modern Predictive Analytics

January 1, 2019

In business, foresight is everything. This guide will help you navigate the modern predictive analytics landscape.


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E-Book: Unlock Big Data Value

January 1, 2019

Download this e-book to discover the right path to big data success for your business.


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Data Protection: Downtime is Money

January 1, 2019

In this paper, we examine the hidden costs for modern data protection and recovery operations.


SAS machine learning white paper cover image

Machine Learning and Artificial Intelligence In a Brave New World

January 1, 2019

Machine learning in the last few decades has given way to an AI revolution. As the amount of data produced continues to scale, use of algorithms enables faster computational understanding to create new opportunities for innovation. From self-driving cars to virtual assistants, the possibilities for these developing technologies are endless.


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