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Trends in Analytics

Data Digest: AI Costs, Myths, and Ethics

Use AI at a reasonable cost, avoid these myths about AI, and learn how AI should be governed to be trustworthy.

Data Digest: Training, Defining, and Applying Machine Learning

Adopting a new machine learning algorithm, defining what kind of machine learning experience you need, and how modern astronomy is using machine learning.

Adopting a Data-Centric Culture (Part 3 in a Series)

In the final part of our series, we look at the characteristics of a data-centric culture and how to adopt such a culture in your own enterprise.

The ABCs of a Data-Centric Culture (Part 2 in a Series)

To become a data-centric enterprise, you must first recognize what counterproductive behaviors you'll need to eliminate.

Why BI Isn't a Technology Issue (Part 1 in a Series)

Implementing a BI program without a data-centric culture is bound to disappoint users and waste resources.

Lessons from Facebook: Can We Defeat Databuse?

We in the information technology and data management disciplines must step up to an engaged and active role in educating the public and businesspeople who are not fully aware of the dangers of abuse of personal and related data.

Data Digest: Machine Learning Pitfalls, Free Training, and Term Definition

How to avoid undermining machine learning, learn the basics online, or find high-level definitions.

Can Automation Accelerate Machine Learning Programs?

Auto ML is a powerful concept for the next generation of AI tools. It's part of a general movement to extend AI-based automation to data science.

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