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TDWI Upside - Where Data Means Business

Executive Perspective: DataOps in Volatile Times

Chris Bergh describes himself as "CEO and Head Chef" of DataKitchen, a company that enables analytics teams to iterate and innovate with their DataOps platform. He shares his enthusiasm for DataOps in this interview, explaining what makes it so popular and what's driving its adoption, as well as how to get the most from AI.

Data Digest: Machine Learning Errors, Sales Applications, IoT for Monitoring

Avoiding machine learning problems, using ML to help sales, and using IoT for machine monitoring.

Data Digest: How Machine Learning Affects Decision Making, Computing Resources, and Coronavirus Testing

Getting started with machine learning, the challenge of training multiple ML models, and how machine learning may improve pooled testing programs.

CEO Perspective: Future Trends in BI and Analytics

What are the big trends enterprises face in BI and analytics? Satyen Sangani, CEO and cofounder of enterprise data catalog vendor Alation, explains why he thinks machine learning, data literacy, data governance, and data catalogs are so important right now.

Data Digest: Data Science Changes, Trends, and Examples

How data science is changing because of COVID-19, data science trends to watch, and how to apply machine learning today.

Executive Perspective: Text, Voice, and Facial Recognition

Natural language processing is helping enterprises analyze their data, but its complexities extend beyond understanding inputs and outputs. Behavioral Signals’ CEO, Rana Gujral, explains NLP’s strengths and weaknesses and compares text, voice, and facial recognition technologies.

Data Digest: Data Governance and Using AI for Security and Privacy

How to communicate the importance of data governance, use machine learning for cybersecurity, and protect data privacy with AI.

Data Digest: Data Science Trouble, ML Flaws, Data Science Culture

How to manage problem areas for data science, compensate for machine learning’s weaknesses, and improve your data culture.

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