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TDWI Upside - Where Data Means Business

Artificial Intelligence (AI) and Machine Learning


Synthetic Data: The Diamonds of Machine Learning

Refined and labeled data is imperative for advances in AI. When your supply of good data does not match your demand, look to synthetic data to fill the gap.

Artificial Intelligence and the Data Quality Conundrum

Garbage training data in, garbage model out. Here are four things to address to solve data quality problems.

Data Digest: Enterprise Structure for ML, Data Organization, and Data Stewardship

Building a great machine learning team, removing data silos, and managing the structure of data governance organizations.

Don’t Start with Data: 3 Tips for Implementing AI Analytics

Focusing on business outcomes, aligning teams, and achieving quick wins can help your AI analytics program succeed.

Data Digest: AI Use Cases, IT and Data Science, Digital Workplaces

New AI-enabled advances, how IT should support data scientists, and how CIOs must face new challenges.

Data Digest: Advanced Analytics Applications in Healthcare

Analytics is used to predict staffing needs, track and analyze symptoms, and identify high-risk patients, but organizations must be wary of bias.

Data Digest: Combining Machine Learning with BI, Finance, and Science

Machine learning has applications across departments and industries. Read examples in these three articles.

Why Enterprises Are Turning to DataOps

Why is DataOps so important for your enterprise data management tasks? We asked Chris Cook, CEO of Delphix and a veteran technology executive with more than 30 years of experience in the enterprise software industry, for his perspective.

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