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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


Beyond Data Governance in the Digital Business

The traditional distinction between governance planning and implementation won't work for data-driven digital businesses.

The New Ethics of Data Management

The hunger for profit is driving the convergence of the digital and physical worlds, which raises some deeply disturbing privacy implications.

Data Models: Beauty Is in the Eye of the Implementer

The data vault model and data warehouse automation are worth investigating if you are about to embark on a new data warehouse project.

The Importance of Being IoT

To win in the marketplace, an organization must incorporate IoT data and analytics, as well as artificial intelligence, into its strategic vision.

Averting Algorithmic Angst

Algorithms may not be as impartial as we think. Avoiding problems with algorithms will demand collaboration and novel thinking across your entire organization.

Making the Most of a Logical Data Warehouse

The logical data warehouse is not a replacement for a traditional data warehouse; it's an extension.

AI in the Crosshairs

At the 2017 World Economic Forum meeting, tech industry leaders openly discussed some of the ethical and societal challenges facing the current surge in big data-driven AI.

Once More into the Data Lake

Data lakes disturb me. It's the shallowness of the definition that concerns me the most.

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