What is the impact of data quality on migration projects?
An example of an AI chatbot conversation about the effects of data quality during migration.
What is the impact of data quality on migration projects?
Data quality is crucial during migration as poor quality can lead to data loss, inaccuracies, and project delays.
Can you give examples of data quality issues that might arise?
Sure! Common issues include duplicate records, incomplete data, and inconsistent formats.
How can we ensure data quality before migration?
Implementing data cleansing processes, validation checks, and thorough testing can help ensure data quality.
What tools can assist in maintaining data quality?
Tools like Talend, Informatica, and Microsoft Azure Data Factory are great for managing and improving data quality.
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