[DataMasters] Getting Data Mastering at Scale Right
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Descripción
What's required to master large numbers of data sources? First, avoid approaches that require writing rules. Then use machine learning and cloud computing to efficiently handle the workload. That advice...
mostra másMike, who's an adjunct professor of computer science at MIT, talks about common data mastering mistakes, why traditional tools aren't right for the task, and shares examples of companies that have successful mastered data at scale.
Información
Autor | PI Media |
Organización | PodIl |
Página web | - |
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