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Welcome to the Data Extraction,Transformation and Loading MCQs Page

Dive deep into the fascinating world of Data Extraction,Transformation and Loading with our comprehensive set of Multiple-Choice Questions (MCQs). This page is dedicated to exploring the fundamental concepts and intricacies of Data Extraction,Transformation and Loading, a crucial aspect of Data Warehousing and OLAP. In this section, you will encounter a diverse range of MCQs that cover various aspects of Data Extraction,Transformation and Loading, from the basic principles to advanced topics. Each question is thoughtfully crafted to challenge your knowledge and deepen your understanding of this critical subcategory within Data Warehousing and OLAP.

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Check out the MCQs below to embark on an enriching journey through Data Extraction,Transformation and Loading. Test your knowledge, expand your horizons, and solidify your grasp on this vital area of Data Warehousing and OLAP.

Note: Each MCQ comes with multiple answer choices. Select the most appropriate option and test your understanding of Data Extraction,Transformation and Loading. You can click on an option to test your knowledge before viewing the solution for a MCQ. Happy learning!

Data Extraction,Transformation and Loading MCQs | Page 7 of 15

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Answer: (c).To standardize measurement units for global operations Explanation:Companies with global operations may need to convert units of measurements to standardize measurement units.
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Answer: (b).To represent date and time in standard formats Explanation:Date/time conversion in data transformation is about representing date and time in standard formats, such as international date formats.
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Answer: (d).Transforming keys with built-in meanings into generic keys Explanation:Key restructuring in data transformation involves transforming keys with built-in meanings into generic keys generated by the system itself.
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Answer: (c).Keeping a single record for a customer and linking duplicates Explanation:Deduplication in data transformation refers to keeping a single record for a customer and linking duplicates from the source systems.
Q65.
What is the primary challenge in ETL functions when dealing with source data from disparate systems?
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Answer: (a).Data integration Explanation:The primary challenge in ETL functions is the integration of source data from disparate systems.
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Answer: (a).Preprocessing source data before applying transformation routines Explanation:Data integration and consolidation involve preprocessing source data before applying major transformation routines.
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Answer: (c).The difficulty of matching records for the same entity across multiple source systems Explanation:The Entity Identification Problem involves the difficulty of matching records for the same entity across multiple source systems.
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Answer: (c).Assigning unique identifiers to all records, whether duplicates or not Explanation:One approach to solving the Entity Identification Problem is to assign unique identifiers to all records, irrespective of whether they are duplicates or not.
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Answer: (b).By assigning unique identifiers in the first phase and reconciling duplicates in the second Explanation:Some companies handle the Entity Identification Problem in two phases by assigning unique identifiers in the first phase and reconciling duplicates in the second.
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Answer: (a).The challenge of handling multiple data sources for the same element Explanation:The Multiple Sources Problem relates to the challenge of handling multiple data sources for the same data element.

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