/plushcap/analysis/acceldata/5-data-quality-issues-and-how-you-can-avoid-them

5 Data Quality Issues and How You Can Avoid Them

What's this blog post about?

Data quality is crucial for businesses to make accurate decisions. Poor data quality can lead to inaccurate analysis, incorrect decisions, and increased security risks. Common data quality issues include incomplete, duplicate, expired, irrelevant, and inaccurate data. To maintain high-quality data, organizations should implement a comprehensive data governance program that includes data quality standards, measurement, and assurance. Data observability tools can help monitor the state and quality of data in real time, enabling businesses to proactively identify potential issues and ensure their data remains accurate, consistent, and reliable.

Company
Acceldata

Date published
April 19, 2024

Author(s)
Eric Goebelbecker

Word count
1248

Hacker News points
None found.

Language
English


By Matt Makai. 2021-2024.