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Health Users Group (HUG) VALIDATING AND CLEANING DATA IN ENTERPRISE GUIDE Judy Orr Lawrence SAS Training Specialist C op yr i g h t 2 0 1 3, S A S I n s t i t u t e I n c. An l r i g h t s res her
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How to fill out validating and cleaning data

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Step 1: Identify the data that needs to be validated and cleaned.
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Step 2: Make sure you have a clear understanding of the data requirements and standards.
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Step 3: Use data validation techniques such as range checks, format checks, and consistency checks to ensure the accuracy and integrity of the data.
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Step 4: Clean the data by removing duplicates, correcting errors, and filling in missing information.
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Step 5: Validate the cleaned data again to ensure it meets the required standards.
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Step 6: Document the validation and cleaning processes for future reference.

Who needs validating and cleaning data?

01
Data analysts
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Data scientists
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Database administrators
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Business analysts
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Data-driven organizations
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Validating and cleaning data involves checking the accuracy, consistency, and completeness of data to ensure it is reliable and free of errors.
Various organizations and businesses may be required to file validating and cleaning data, depending on industry regulations and internal data management processes.
Validating and cleaning data involves using software tools and manual checks to identify and correct errors, inconsistencies, and missing information in datasets.
The purpose of validating and cleaning data is to improve data quality, enhance decision-making, and ensure compliance with data integrity standards.
Information reported on validating and cleaning data may include data validation results, error logs, data cleaning procedures, and quality assurance measures.
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