Assessing Data Quality: Best Practices

You are a data quality consultant tasked with helping a company improve their data management processes. Develop a comprehensive guide for assessing and maintaining data quality, focusing on best practices for regular audits and validation techniques. Include detailed steps for identifying common data quality issues, methods for evaluating data integrity, and strategies for continuous improvement. Provide examples of validation techniques such as cross-verification, outlier detection, and accuracy checks, and suggest tools or software that can aid in these processes. Tailor your advice for a team managing large datasets across both databases and spreadsheets, ensuring clarity and applicability.