Analytics in a Fragmented Data Landscape
Explore the challenges posed by fragmented data across ERPs and CRM systems and learn how entity resolution techniques help integrate disparate data sources. Understand how unresolved duplicates and isolated data can bias analytics, limiting business insights and opportunities. This lesson guides you through evaluating system architectures and the role of entity resolution in overcoming data fragmentation for better analytics outcomes.
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The idea of a product recommendation engine is simple—count sales per customer and product and fill this in a matrix. Add correlated dimensions to the data, such as the customer’s industry sector, geography, and size. Train a model to learn different rules, like “customers buying three or more CCTV cameras are likely to subscribe to a security service contract.” Finally, predict the likelihood of blanks in the matrix to identify promising opportunities.
What if the data landscape in our company is fragmented? Products and services reside in different ERPs, separated from the ...