An embedding driven approach to automatically detect identifiers and references in document stores
NoSQL stores have become ubiquitous since they offer a new cost-effective and schema-
free system. Although NoSQL systems are widely accepted today, Business Intelligence &
Analytics (BI&A) wields relational data sources. Exploiting schema-free data for analytical
purposes is a challenge since it requires reviewing all the BI&A phases, particularly the
Extract-Transform-Load (ETL) process, to fit big data sources as document stores. In the ETL
process, the join of several collections, with a lack of explicitly known join fields is a …
free system. Although NoSQL systems are widely accepted today, Business Intelligence &
Analytics (BI&A) wields relational data sources. Exploiting schema-free data for analytical
purposes is a challenge since it requires reviewing all the BI&A phases, particularly the
Extract-Transform-Load (ETL) process, to fit big data sources as document stores. In the ETL
process, the join of several collections, with a lack of explicitly known join fields is a …
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