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#78 - Data Warehousing in 2022, Textual ETL, and More w/ Bill Inmon
Monday Morning Data Chat
Textual Disambiguation vs NLP
Textual disambiguation differs from NLP in its original purpose and commercialization. NLP was designed for language study, not commercial use, and transforming it into a commercial product is challenging. NLP is expensive, time-consuming, and complex, while textual disambiguation is inexpensive, fast, and simple, with a focus on being a commercial product. Forest Rim Technology is recommended for textual disambiguation in healthcare and customer feedback analysis. Adoption of textual disambiguation is driven by end-users like doctors, hospital administrators, and marketing professionals rather than IT technicians, similar to the early acceptance pattern of data warehousing.
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