Microsoft Fabric Analytics Engineer Associate DP-600
Litware, Inc., a prominent manufacturing company with offices spread across North America, employs a diverse analytics team consisting of data engineers, analytics engineers, data analysts, and data scientists. As part of their new initiative, Litware aims to enable Fabric features within their existing tenant and establish a new data store as a proof of concept (PoC). To facilitate data ingestion into this new data store, especially in the AnalyticsPOC workspace, the data engineers plan to utilize low-code tools wherever feasible. What would you recommend for effectively ingesting customer data into the data store in the AnalyticsPOC workspace?
Exam-Like
A
a stored procedure
B
a pipeline that contains a KQL activity
C
a Spark notebook
D
a dataflow
Explanation:
The data engineers at Litware are instructed to use low-code tools for data ingestion whenever possible. Dataflows are a suitable option because they allow for low-code ETL (Extract, Transform, Load) processes, making it easier to ingest, transform, and load data without extensive coding. Other options like stored procedures, pipelines with KQL activities, and Spark notebooks require more coding effort and do not align with the requirement of using low-code tools.