![]() ![]() In my new world, Grubhub defines database tables with a Hive metadata layer and a Presto DB engine on top to facilitate data analysis with SQL. They emphasized understanding business processes as part of the report cube design. In the world of my old job, all databases were relational and visual tools provided enhanced modelling and construction. At my previous job, I designed and built enterprise data warehouses (EDW) for Fortune 100-type clients using business intelligence (BI) tools supplied by SAP and Oracle. I’m a relatively new data engineer at Grubhub - this means I needed to quickly learn how to use Apache Spark, which is the data processing engine our Enterprise Data Warehouse runs on.
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