Suggested Answer:
Extract, transform, and load (ETL) is a data pipeline used to collect data from various sources, transform the data according to business rules, and load it into a destination data store. Reference: https://docs.microsoft.com/en-us/azure/architecture/data-guide/relational-data/etl
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.
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
Correct Answer
ELT-a target data store powerful enough to transform data.
ETL-data that is fully processed before being loaded to the target data store.
ETL - Extract then Transform the Load - It always ensure apply all the transformation logic after extracting/bore loading into Target table. Target table is ready to use the data for reporting/visualizations. My preference is "C"
Pretty similar to Qst#31 (ELT there). Here ETL.
It will be understandable if you take "transform" and "process" as equivalent.
And then yes, process/transform is before load.
And on ELT (Qst#31): yes, for transform/process the target needs capabilities for it.
Missleading because question is about "requires" (=prerequisite) and then the answer "fully processed before". Extraction belongs to processing (ETL or ELT). So why should that have startet after "FULLY processed before"?
The answer has to be C.
Microsoft trainer handbook describes ETL as raw data being retrieved and transformed before being saved. The book also states that ELT is data stored before being transformed. Although the question is poorly articulated, I would choose C in this case.
I think this is a misleading question. Clearly it is not A or D. ETL process can be run in parallel to save time. While data is being extracted, a transformation process could be working on data already received and prepare it for loading, and a loading process can begin working on the prepared data, rather than waiting for the entire extraction process to complete. (https://docs.microsoft.com/en-us/azure/architecture/data-guide/relational-data/etl). This suggests that C is also incorrect.
This leaves B. By the book, this would be correct for ELT but appears incorrect for ETL because the transformation process occurs in an isolated specialized engine prior to loading. However, in reality, a lot of older ETL routines are actually ELT based on their infrastructure. Therefore, I would be inclined to go for B.
Nonetheless another poorly chosen question though.
Transform mean processed. so the answer should be B
upvoted 3 times
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