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TDWI Articles

Contributor: Barry Devlin


Dr. Barry Devlin, founder and principal of 9sight Consulting, is among the foremost authorities on business insight and big data, and is one of the founders of data warehousing, having published the first architectural paper on the topic in 1988. With over 30 years of IT experience, including 20 years with IBM as a Distinguished Engineer, he is a widely respected analyst, consultant, lecturer and author of the seminal book, “Data Warehouse—from Architecture to Implementation” and numerous White Papers. His new book “Business unintelligence—Insight and Innovation beyond Analytics and Big Data” is published later this year. A regular contributor to multiple publications, Barry is based in Cape Town, South Africa and operates worldwide.

  


All articles by Barry Devlin


The Data-Driven Fascination with Now

Human biases are easily skewed by newer data because it makes up an ever-larger proportion of the data landscape.

IBM Doubles Down on AI

Despite the attraction of consumer-facing AI, IBM's focus on practical business applications may yet win the race for widespread AI adoption.

Google Ups the Ante on AI

Google forges ahead with powerful techniques and discoveries in artificial intelligence. Where are examples of their application to BI to be seen?

Fake News: Analytics Only Scratches the Surface

Current attempts to weed out fake news focus on analytics and algorithmic approaches. They miss more intractable social and psychological issues that must be addressed.

The Problem with Bimodal IT

Bimodal IT cannot deliver on its aims because it misses the organizational and personal aspects of an integrated, high-speed, digital business.

More Big Databuse

The use and abuse of AI-based chatbots and avatars powered by your own big data may threaten democracy by the 2020 U.S. election far more than this year's fake news.

Data Models Will Be Beautiful Again

Data modeling has fallen out of favor with the rise of big data, but the context provided by modeling will be critical to successful AI applications and algorithm-based decision making.

Big Databuse

With so many election predictions gone wrong, what are the lessons for business use of big data?

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