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Microsoft Certified: Azure Data Fundamentals · Microsoft
Hot Area / Sentence Completion
Select the appropriate option to complete the statement. Click Check Answer below to see the marked solution.
Hotspot Solution:
a. a matching schema in the data source and the data target Incorrect. While having a well-defined schema can help, ETL processes are designed to handle differences between schemas in the source and target. ETL can transform data to fit the target schema. b. a target data store powerful enough to transform data Incorrect. ETL processes transform data in transit, typically in an ETL tool or engine, before loading it into the target data store. The transformation does not rely on the processing power of the target store. c. data that is fully processed before being loaded to the target data store Correct. In a typical ETL process, data is extracted from the source, transformed as needed (e.g., cleaned, aggregated, formatted), and then loaded into the target data store. d. that the data target be a relational database Incorrect. The target data store can be various types, including relational databases, data lakes, or NoSQL databases. ETL processes are not limited to relational databases.
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a. a matching schema in the data source and the data target Incorrect. While having a well-defined schema can help, ETL processes are designed to handle differences between schemas in the source and target. ETL can transform data to fit the target schema. b. a target data store powerful enough to transform data Incorrect. ETL processes transform data in transit, typically in an ETL tool or engine, before loading it into the target data store. The transformation does not rely on the processing power of the target store. c. data that is fully processed before being loaded to the target data store Correct. In a typical ETL process, data is extracted from the source, transformed as needed (e.g., cleaned, aggregated, formatted), and then loaded into the target data store. d. that the data target be a relational database Incorrect. The target data store can be various types, including relational databases, data lakes, or NoSQL databases. ETL processes are not limited to relational databases.
ETL stands for extract, transform, and load. So, data must be transformed before loading. Therefore, the third option is correct.
Answer is correct -C. - BEFORE the Data store - Extract, load, transform (ELT) differs from ETL solely in where the transformation takes place. In the ELT pipeline, the transformation occurs in the target data store. - This question asks - before being loaded not "in" the data store - Which is ETL