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Thinking about deep machine learning, how ready is your data (cleaned, prepped and labeled) for compute-heavy data models?

Probably depends on age and size of business. Ours has divisions over 100 years old or acquired less than 2 years ago. We struggle with data quality even within a division. Note that our smallest is probably 25,000 employees and largest 40,000. Total company 130k people, 15 major ERPs and probably 20 minor ERPs. We still have debates on Customer address and shipping fields sometimes during consolidations. My estimate 35% of the data we would like to use is ready

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Probably depends on age and size of business. Ours has divisions over 100 years old or acquired less than 2 years ago. We struggle with data quality even within a division. Note that our smallest is probably 25,000 employees and largest 40,000. Total company 130k people, 15 major ERPs and probably 20 minor ERPs. We still have debates on Customer address and shipping fields sometimes during consolidations. My estimate 35% of the data we would like to use is ready
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