Ingest and Transform Data DP-203 Practice Questions (Page 1)

Questions 1–5

1. 1foundation · easy

   Which Azure Stream Analytics feature helps achieve Exactly Once Delivery by storing state and enabling recovery?

   • AEvent Hub partitioning
   • BCheckpointing and state management
   • CReference data joins
   • DWindowing functions
   Reveal Solution Discussion Select an answer first
2. 2application · medium

   A marketing company loads customer data from a CRM into Azure Synapse Analytics daily. The CRM exports full snapshots, and the same customer can appear multiple times with different updated timestamps. You need to ensure that only the latest version of each customer is stored in the target table. What should you do?

   • AUse a Copy activity with a query that uses SELECT DISTINCT on all columns.
   • BUse a Stored Procedure that deletes all rows and reloads the entire snapshot each day.
   • CUse a Data Flow transformation with a RowNumber over PartitionBy customer ID ordered by updated timestamp descending, then filter to RowNumber = 1.
   • DUse a Lookup activity to get the maximum timestamp and then copy only rows with that timestamp.
   Reveal Solution Discussion Select an answer first
4. 3foundation · easy

   Why might you need to encode data during data processing?

   • ATo permanently delete data from the system
   • BTo increase the size of the data
   • CTo make data unreadable to anyone
   • DTo convert data into a format that is safe for transmission or storage
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5. 4expert · hard

   A retail analytics team has a denormalized table in Azure Synapse Analytics with repeated product and store information for every sales transaction. The table is used for both detailed sales analysis and reporting. You need to reduce data redundancy and improve data integrity while maintaining query performance for the reporting workload. What should you do?

   • ASplit the table into multiple smaller tables based on product category and store region.
   • BNormalize the table into separate fact and dimension tables and use views to join them for reporting.
   • CKeep the denormalized table and add more indexes to improve query performance.
   • DUse a materialized view to pre-aggregate the data and keep the denormalized table as-is.
   Reveal Solution Discussion Select an answer first
6. 5foundation · easy

   What is the purpose of data splitting in a data processing pipeline?

   • ATo combine multiple data sources into one dataset
   • BTo divide data into subsets for separate processing or analysis
   • CTo compress data to save storage space
   • DTo encrypt data for secure transmission
   Reveal Solution Discussion Select an answer first