What are common data quality issues in analytics?
An example of an AI chatbot conversation about data quality issues in analytics.
What are common data quality issues in analytics?
Common data quality issues include missing data, duplicate records, inconsistent formats, and inaccurate data.
How can I identify these issues in my dataset?
You can use data profiling techniques, validation rules, and automated tools to identify data quality issues.
What tools do you recommend for data quality management?
Some popular tools include Talend, Informatica, and Trifacta, which help in cleansing and managing data.
Can you explain how to fix missing data?
You can fix missing data by using techniques like imputation, data interpolation, or simply removing incomplete records.
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