Standardizing Your Approach to Monitoring the Quality of Data

Blog Administrator | Address Standardization, Analyzing Data, Data Cleansing, Data Integration, Data Management, Data Profiling, Data Quality | , , , , , , ,

By David Loshin

In my last post, I suggested three techniques for maturing your organizational approach to data quality management. The first recommendation was defining processes for evaluating errors when they are identified. These types of processes actually involve a few key techniques:

1) An approach to specifying data validity rules that can be
used to determine whether a data instance or record has an error.

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Four Pillars of Data Quality Improvement

Blog Administrator | Analyzing Data Quality, Data Integration, Data Management, Data Profiling, Data Quality | , , , ,

By Elliot King

Almost all data quality management programs have four key elements that serve as the foundations for success–data profiling, data improvement, integration and data augmentation. Put in other words, data quality programs must determine what is broken; fix what can be fixed; consolidate what can be consolidated and enhance what needs to be enhanced. Sounds easy, right? If only.
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The Role of Data Profiling in Data Quality Assessment

Blog Administrator | Data Profiling, Data Quality, Data Quality Assessment | , ,

By Elliot King

After
“sustainability,” perhaps the biggest buzzword flying around many corners of the
corporate world these days is assessment. It seems people can’t breathe without
somebody wanted to assess the quality of the air, the efficiency of their lungs,
and, of course, the outcome of the breath.

But just because something is a buzzword, doesn’t mean it is a bad thing.… Read More