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TDWI Upside - Where Data Means Business

Practical Data Science


Data Digest: Data Difficulties, AI Risks, Adjusting ML

Determining when data can’t solve a problem, identifying the dangers of generative AI, and removing outdated or inappropriate training data from machine learning systems.

Data Stories: Parks, Games, and Toys

These data visualizations show amusement park attendees, video game sales, and Barbie’s careers.

Three Things Leaders Must Consider for the Coming Age of Artificial General Intelligence

Artificial general intelligence, a term coined by scientists, describes computing systems that could eventually be as smart as humans. Practically speaking, what does this mean, and what are its implications?

Data Digest: Security, AI, City Planning

Learning from previous cybersecurity failures, creating a successful AI solution at a bank, and creating a vision of future cities.

Data Stories: Box Office Records and Other Movie Money

Visualizing recent box office returns, one movie star’s career, and the different ways to measure a successful film.

Clearing Up Cloud Confusion for Data Warehousing (Part 2 of 2)

Before moving your data warehouse or lake to the cloud, it’s vital to have clear skies and a good view of the horizon.

How to Succeed with Unifying DataOps and MLOps Pipelines

James Kobielus, TDWI’s senior research director for data management, discusses the opportunities and challenges associated with enterprise unification of DataOps and MLOps pipelines.

Cloud Confusion for Data Warehousing (Part 1 of 2)

If you are planning to move your data warehouse or data lake to the cloud, the current outlook is somewhat foggy.

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