This session explores how Cambridge Mobile Telematics (CMT) uses Amazon Redshift for large-scale geospatial and text data analysis. We'll discuss why CMT chose AWS and Redshift based on scalability and integration needs, highlighting how Redshift's geospatial solution using H3 functions enable efficient processing of billions of location records. The presentation demonstrates CMT's use of Redshift's NLP capabilities, featuring QEv2 and Vega for advanced ad-hoc reporting. Finally, we examine how Redshift's architecture delivers the optimal price-performance balance for CMT's demanding data operations.

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