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Five Fundamental Data Quality Practices W H I T E PA P E R : DATA QUALITY & DATA INTEGRATION David Loshin WHITE PAPER: DATA QUALITY & DATA INTEGRATION Five Fundamental Data Quality Practices 2 INTRODUCTION
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What is five fundamental data quality?
Five fundamental data quality refers to the five key attributes that determine the quality of data. These attributes include accuracy, completeness, consistency, validity, and uniqueness.
Who is required to file five fundamental data quality?
The requirement to file five fundamental data quality depends on the specific regulations or policies set by the governing body or organization. It may vary depending on the industry or jurisdiction.
How to fill out five fundamental data quality?
Filling out five fundamental data quality involves ensuring that data is accurate, complete, consistent, valid, and unique. It requires thorough data validation processes, proper data entry procedures, and adherence to data quality standards.
What is the purpose of five fundamental data quality?
The purpose of five fundamental data quality is to ensure that data is reliable, usable, and of high quality. It helps organizations make informed decisions, improve operational efficiency, mitigate risks, and comply with regulatory requirements.
What information must be reported on five fundamental data quality?
The specific information required to be reported on five fundamental data quality depends on the context and purpose of data quality assessment. It typically includes details on the accuracy, completeness, consistency, validity, and uniqueness of the data.
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