Use Data Acquisition Methods DA0-001 Practice Questions (Page 5)

Questions 21–25

1. 21application · easy

   A data analyst is integrating customer data from two systems. System A has a field `cust_id` (integer), and System B has a field `CustomerID` (string). The analyst needs to create a unified dataset. What is the first step in the data mapping process?

   • ALoad both datasets into a data warehouse and hope the fields align
   • BConvert all data to XML format
   • CDefine the relationship between `cust_id` and `CustomerID` and determine the target field name and data type
   • DDelete the `CustomerID` field from System B to avoid conflicts
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2. 22foundation · easy

   During data integration, which validation technique ensures that a foreign key value in a table has a corresponding primary key in the referenced table?

   • AUniqueness check
   • BData type check
   • CRange check
   • DReferential integrity check
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4. 23foundation · easy

   A dataset contains duplicate customer records. Which data cleansing technique should be applied to remove these duplicates?

   • AData deduplication
   • BData normalization
   • CData imputation
   • DData transformation
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5. 24application · medium

   During an ETL process, a data engineer loads a table and then runs a query that counts the number of rows in the source and the target. The counts match, but a subsequent analysis finds that some values in a `price` column are negative, which is impossible for the business. Which data validation step was likely missed?

   • AChecksum validation
   • BSchema validation
   • CBusiness rule validation
   • DRecord count validation
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6. 25application · medium

   A data engineer is integrating data from two source systems. System 1 uses `employee_id` as a unique identifier, and System 2 uses `emp_no`. Both refer to the same employee. The engineer needs to create a unified view. What is the most critical step to ensure the data is correctly combined?

   • AUse a fuzzy matching algorithm to join the datasets
   • BLoad both datasets into a data lake and use a schema-on-read approach
   • CCreate a data mapping that defines `employee_id` from System 1 as equivalent to `emp_no` from System 2
   • DRename all fields in System 2 to match System 1
   Reveal Solution Discussion Select an answer first