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TDWI Upside - Where Data Means Business

Practical Data Science

Four Tips to Modernize Legacy ETL Processes

Modernizing ETL, especially the underlying infrastructure that supports it, across all your lines of business is vital for enhancing downstream analytics and decision-making.

Building an AI Strategy with Caroline Carruthers

Before jumping into AI, it’s important to have a strategy. You need to know what problem you are trying to solve, where you are now, and where you want to go. The CEO of global data consultancy Carruthers and Jackson explains what’s involved in building this strategy and where AI -- not just generative AI -- is headed.

Q&A: Can Neuro-Symbolic AI Solve AI’s Weaknesses?

Neuro-symbolic AI integrates several technologies to let enterprises efficiently solve complex problems and queries demanding reasoning skills despite having limited data. Dr. Jans Aasman, CEO of Franz, Inc., explains the benefits, downsides, and use cases of neuro-symbolic AI as well as how to know it’s time to consider the technology for your enterprise.

Data Stories: Functions and Risks of Generative AI

How large language models work, fake AI charts, and bias in the model.

Data Stories: Solstices and Solar Eclipses

How leap day impacts the calendar and two maps for the 2024 solar eclipse.

Can Synthetic Data Jumpstart Your Strategic Projects?

Don’t let sparse data derail your analytics projects. Synthetic data can fill the gaps, but choosing the right generation method is key. Explore rule-based, statistical, and GAN approaches -- with their benefits and trade-offs.

Data Digest: Industries Applying AI Today

AI and generative AI applications in the legal, healthcare, and automotive industries.

Data Stories: Historical Visualizations and Old UI

Check out early data visualizations, historical infographics, and the history of scroll bars.

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