Conditional Split Transformation | Data Flows | Azure Data Factory (ADF) | Azure Data Engineer (ADE)
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👉 What is conditional split transformation in Azure Data Factory (ADF)?
The conditional split transformation routes data rows to different streams based on matching conditions. The conditional split transformation is similar to a CASE decision structure in a programming language. The transformation evaluates expressions, and based on the results, directs the data row to the specified stream. Let us see practically how to create and use conditional split transformation in Azure for Data Factory.
👉 What is Azure Data Engineer?
Azure data engineers help stakeholders understand the data through exploration, and they build and maintain secure and compliant data processing pipelines by using different tools and techniques. Azure data engineers also help to ensure that the operationalization of data pipelines and data stores are high-performing, efficient, organized, and reliable, given a set of business requirements and constraints.
👉 What is Azure Data Factory?
Data originating from various sources is crucial to the current state of information technology. This data must be processed in order to be organized and made useable. It may be organized or unstructured, kept locally or on the cloud, etc. It is a laborious and expensive effort to work on all of these data to offer a consistent data flow. Where Azure Data Factory comes into play is in this situation.
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