Glue Data Quality
Data Quality is fundamental for a variety of reasons, spanning across business, science, government, and numerous other sectors. There are many reasons why it is essential to maintain high data quality, including:
- Conveying business decisions: business decisions must be based on accurate and reliable data. Low quality data could lead to incorrect decisions that negatively impact business operations.
- Precise analyses: data analysis is a fundamental part of many business activities. Low-quality data could lead to inaccurate results and misinterpretations.
- Regulatory compliance: many companies are subject to strict regulations on data management. Lack of data quality could lead to regulatory violations and financial penalties.
- Time savings and efficiency: high-quality data simplify business processes. Cleaning and correcting data takes significant time and effort. High-quality data therefore reduce the need for such activities.
- Customer satisfaction: data quality directly affects customer satisfaction. Incorrect data can lead to errors in customer reports and communications.
What is AWS Glue Data Quality?
AWS Glue Data Quality is a feature of AWS Glue, Amazon’s fully managed extract, transform, and load (ETL) service. This feature provides users with the ability to validate and monitor the quality of data sources, making it easier to maintain high-quality data for analytics and machine learning applications.
Below are the main features of Glue Data Quality.
Automatic recommendations of custom rules for your data
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