“You can’t manage what you don’t measure” – a quote made famous by business management expert Peter Drucker – rings true to most work done in product and service quality. If you’re not measuring and tracking your progress, what you’re doing isn’t much better than guessing.
Key Performance Indicators and other quantitative and qualitative measures help nearly every industry align on standards around product or service quality – from automotive to healthcare to CPG. With the advance of data & analytics beyond reporting to AI enablement, scoring data for its quality is a non-negotiable.
Understanding the quality and trendlines of your data is imperative to proactively managing your data at scale. At Qualytics, we are advancing how businesses measure and enhance their data’s integrity with our innovative Quality Score Factors. There is no one aggregate score that will be adequate to measure Quality, and different parts of the Quality formula matter differently to various teams. This blog post explores how our innovative scoring system empowers organizations to establish baselines across categories, tailor their data quality assessment and ultimately foster a culture of continuous improvement.
Introducing Data Quality Measurement
It is impossible to define one score that can be a fit to all organizations. Some will emphasize similar shapes & patterns of data arriving at the right time, whereas others may emphasize formats and standards of 3rd party data arriving to their data ecosystem more. Recognizing this challenge, Qualytics has developed a framework that enables measurement across the eight fundamental categories of data quality, while enabling a customized rollup per organization:
- Accuracy: Your data represents the true real-world values
- Completeness: Required fields are all populated with values
- Coverage: Availability and uniqueness of expected records
- Conformity: Alignment of the content to the required standards
- Consistency: Values are the same for all copies and representations
- Precision: Your data is of the expected defined resolution
- Timeliness: Data is available when and where you expect it
- Volumetrics: Data has the same size and shape across similar cycles
Each of these categories is measured and represented separately for each field, container, and datastore, providing a granular view of data health across the data ecosystem. This method enables organizations to establish specific baselines and track improvements over time, ensuring a thorough understanding of each data element’s quality.
The Impact Of Quality Score Factors
The introduction of Quality Score Factors marks a significant leap in proprietary data quality measurement. This level of customization, highlighted below, is crucial for making quality scoring more relevant and actionable across different business use cases.
Key Capabilities Of The New Quality Score System:
- Customizable Factor Weights: Users can define their own formulas for quality scores by adjusting the weights of different factors at the Datastore and Container levels. This flexibility allows for precision in how data quality is assessed, aligning it more closely with organizational goals.
- Quality Score Detail Expansion: By clicking on the quality score number, users can expand its details to see how each factor contributes to the overall score. This feature not only enhances transparency but also helps users pinpoint areas needing improvement.
- Enhanced Inferred Checks: We’ve introduced improvements in the Check Listing schema and the Check modal, including new validity metrics that help quantify the accuracy of inferred checks.
Qualytics Data Quality Score Meets Business Strategy
By providing a detailed and customizable approach to measuring data quality, Qualytics helps businesses leverage their data more effectively. Whether it’s disregarding the Timeliness factor for dimension tables where it’s irrelevant, or emphasizing Accuracy in transactional data, the ability to fine-tune quality scoring ensures that businesses can focus on what truly matters to them.
In today’s AI and data-driven environment, the ability to precisely measure and improve data quality is not just an operational need—it’s a strategic advantage. Qualytics is proud to lead the charge towards more scalable and effective data quality frameworks.
Our next generation of quality scoring embodies our commitment to data excellence. With Quality Score Factors, organizations gain unprecedented control over their data quality measures, empowering them to make informed decisions and drive continuous improvement.
Reach out to us today to discuss our proprietary Quality Score and how it can impact your business.
