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TDWI Upside - Where Data Means Business

Achieving Success with Modern Analytics (Part 1 of 2)

Fern Halper, TDWI’s vice president and senior director of research for advanced analytics, discusses her recent TDWI Best Practices Report on achieving success with modern analytics -- including exciting use cases and common challenges organizations need to overcome.

Generative AI and Its Implications for Data and Analytics

Generative artificial intelligence has captured the imaginations of people around the world. Though not entirely new, generative AI is evolving so rapidly that technology professionals need to track its maturation closely to effectively evaluate the associated opportunities and risks. Here are the basics you need to know.

Data Stories: Stylish, Effective Data Visualizations

Making a data visualization elegant, conveying insights clearly, and choosing a visualization tool.

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Determining when data can’t solve a problem, identifying the dangers of generative AI, and removing outdated or inappropriate training data from machine learning systems.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

What you should know about MLOps, boosting ML models, and putting ML on smartphones.

Data Stories: Parks, Games, and Toys

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

Q&A: An Introduction to Streaming AI

Generative AI is getting all the buzz lately, but a different kind of AI -- streaming AI -- may have a greater impact on an enterprise’s analytics. Lenley Hensarling, chief product officer at Aerospike, explains.

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?

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