Spotlight on 3E's Commitment to Quality: The Top Six Data Quality Dimensions

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October 28, 2016 - Elliot Martinez

3E Company has achieved best-in-class data quality by maintaining a focus on six key data quality dimensions. Prioritizing and emphasizing quality control helps ensure that 3E provides our valued clients with data of the highest quality and integrity. As a result of our efforts, our customers can be confident that the data managed by 3E is accurate and reliable. 

In order to achieve the highest level of data quality, it is crucial that data is analyzed with six key characteristics in mind, including:

  1. Completeness – in some cases, missing data is irrelevant but when missing information is critical to specific business processes, completeness becomes an issue. With this in mind, the 3E team reviews data to ensure that all requisite information is available and determine if any key data values are missing or unusable. 
  2. Conformity – maintaining conformity to specific formats is important in data representation, presentation, aggregate reporting, search and establishing key relationships. When reviewing data, our team considers whether data values need to conform to specified formats and, if so, we ensure that the values conform to the appropriate format. 
  3. Consistency – inconsistency between data values plagues organizations attempting to reconcile different systems and applications. 3E’s experts evaluate whether distinct data instances provide conflicting information about the same underlying data object, analyzing whether values are consistent across data sets. We also ensure that interdependent attributes appropriately reflect their expected consistency.
  4. Accuracy – incorrect spellings of product or person names and addresses and even untimely or outdated data can impact operational and analytical applications. Our team is diligent in reviewing data objects to ensure they accurately represent the “real-world” values they are expected to model.
  5. Duplication – the inability to maintain a single representation for each entity across systems poses numerous vulnerabilities and risks. 3E helps mitigate this risk by reviewing data to ensure there aren’t multiple, unnecessary representations of the same data objects within a data set.
  6. Integrity – the inability to link related records together may actually introduce duplication across systems. As more value is derived from analyzing connectivity and relationships, the inability to link related data instances together impedes this valuable analysis. Our team adds value by analyzing data to determine what data is missing important relationship linkages. 

Each year 3E Company manages eight to nine terabytes of data. Although maintaining a high level of quality for this amount of data is a daunting task, 3E strives to provide world class products and service to all of our clients. Our efforts to ensure consistency and data validation by applying document and data scanning algorithms are evidence of our commitment to excellence.

If you have any questions, or would like to learn more, please leave us a comment on this post.

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