The process of cleansing and transforming big datasets in the data lake has become an increasingly popular and critical step in a modern enterprise’s data architecture. Microsoft has introduced several big data analytics and orchestration tools to serve the need for big data lake Extract-Load-Transform (ELT). Customers are seeking cloud-based services that can cleanse, transform, and aggregate extremely big datasets with ease, coupled with a low learning ...
© The Author(s), under exclusive license to APress Media, LLC, part of Springer Nature 2021
R. C. L'EsteveThe Definitive Guide to Azure Data Engineeringhttps://doi.org/10.1007/978-1-4842-7182-7_1212. Aggregate and Transform Big Data Using Mapping Data Flows
Ron C. L’Esteve1
(1)
Chicago, IL, USA
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