Build Data Pipelines for Data Science Workloads SNOWPRO-ADVANCED-DATA-SCIENTIST Practice Questions (Page 3)

Questions 11–15

1. 11application · medium

   A data pipeline runs a series of SQL transformations and a Snowpark script to generate features. The team wants to orchestrate this pipeline entirely within Snowflake, with the ability to retry failed steps. Which feature should they use?

   • AA stored procedure that calls all steps sequentially.
   • BSnowflake Tasks with a DAG (task graph) and retry policies.
   • CSnowpipe to load data and trigger transformations.
   • DExternal orchestration tool like Airflow with Snowflake operators.
   Reveal Solution Discussion Select an answer first
2. 12foundation · easy

   Which Snowpark API method is used to remove duplicate rows from a DataFrame?

   • Aunique()
   • Bdistinct()
   • Cdeduplicate()
   • Ddrop_duplicates()
   Reveal Solution Discussion Select an answer first
4. 13foundation · easy

   Which Snowpark ML function is used to create a new feature by combining existing columns, such as calculating a ratio?

   • Acol()
   • Bwith_column()
   • Cfilter()
   • Dselect()
   Reveal Solution Discussion Select an answer first
5. 14foundation · easy

   Which sequence correctly represents the typical order of stages in an end-to-end data pipeline for a data science workload?

   • AIngestion → Transformation → Feature Engineering → Model Training
   • BTransformation → Model Training → Ingestion → Feature Engineering
   • CModel Training → Feature Engineering → Transformation → Ingestion
   • DFeature Engineering → Ingestion → Model Training → Transformation
   Reveal Solution Discussion Select an answer first
6. 15foundation · easy

   What is the primary purpose of setting up monitoring for a data pipeline?

   • ATo detect and diagnose issues in pipeline execution
   • BTo encrypt data in transit
   • CTo reduce storage costs
   • DTo automatically fix data quality issues
   Reveal Solution Discussion Select an answer first