Data Quality Monitoring Using Quality Indicators

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Discover how to optimize your business management with the quality indicators we propose to quantify data quality performance.
Quality indicators used to monitor data quality have the potential to become important business performance indicators.

Poor data quality impacts both operational activities and strategic initiatives , and the process used to assess business impact and justify data quality improvement can in turn be used to monitor ongoing data quality management. By relating business impact to data quality indicators , the enterprise can use these quality indicators to both achieve a baseline measure and to continuously monitor data quality performance.

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Quality indicators to quantify data quality performance
How can an organization's data quality performance be quantified? What metrics enable this insight? Choosing relevant quality indicators associated with well-defined data quality dimensions will help czech republic number dataset the company's progress in this regard, revealing everything there is to know about its performance.

To proceed with the establishment of these quality indicators, the following steps must be followed:

Identify key data sets associated with business policies.

Determine how these relate to the quantifiable impact of the business.

Define dimensions and specify rules that enable you to monitor occurrences and evaluate how identified data defects are classified within a quality data set.

Quantify the contribution of each defect to compliance with each business policy.

Create a management framework in which data rules are articulated and implemented.
This process will result in the extraction of different data quality indicators that will facilitate measuring general compliance with business policies within different categories.

And so, once you've broken down data problems into a number of key attributes , it becomes easier to determine where to focus your efforts and what measures to prioritize.