ETL stands for Extract, Transform, Load, which are the three fundamental steps in the data integration process:
Extract:Retrieving data from various source systems.
Transform:Cleaning and converting the extracted data into a suitable format or structure for analysis.
Load:Inserting the transformed data into a target database or data warehouse.
Option A:Reviewing and addressing missing values
Rationale:During theTransformphase of the ETL process, data is cleansed and prepared for analysis. This includes reviewing and addressing missing values to ensure data quality and consistency. Handling missing data is crucial, as it can impact the accuracy of analyses and decision-making.
[Reference:The CompTIA Data+ Certification Exam Objectives highlight the importance of data cleansing and profiling during the transformation phase of the ETL process., comptia.org, Option B:Creating a dashboard, Rationale:Creating a dashboard is part of data visualization and reporting, which occurs after the ETL process has been completed. Dashboards are tools used to present data insights and are not involved in the extraction, transformation, or loading of data., Option C:Inserting a pivot table and pivot chart, Rationale:Inserting pivot tables and pivot charts is an analytical activity performed on processed data, typically after the ETL process. These tools help in summarizing and analyzing data but are not part of the ETL stages., Option D:Multiplying unique data, Rationale:This option is ambiguous and does not correspond to any standard activity within the ETL process., , ]
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