After the daily ETL jobs are completed, the data in the reports does not appear complete, and a lot of data seems to be missing. Which of the following concepts should be used to assess and…

The correct answer is B. Data profiling. Data profiling is the process of examining a dataset to understand its structure, completeness, content, and quality. After an ETL (Extract, Transform, Load) job produces incomplete results, data profiling helps you investigate by checking record counts, identifying missing…

Data Governance, Quality, and Controls

Question

After the daily ETL jobs are completed, the data in the reports does not appear complete, and a lot of data seems to be missing. Which of the following concepts should be used to assess and investigate further?

Options

ACross-validation
BData profiling
CData integrity
DData consistency

How the community answered

(23 responses)

A
13% (3)
B
74% (17)
C
4% (1)
D
9% (2)

Explanation

Data profiling is the process of examining a dataset to understand its structure, completeness, content, and quality. After an ETL (Extract, Transform, Load) job produces incomplete results, data profiling helps you investigate by checking record counts, identifying missing fields, and comparing source data to destination data. Cross-validation is a machine learning technique, data integrity ensures data is accurate and consistent over its lifecycle, and data consistency checks whether data matches across systems. Data profiling is the correct investigative tool for diagnosing incomplete ETL output.

Topics

#Data Profiling#ETL#Data Quality#Missing Data

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