The Many Dimensions of Data Quality

Melissa IN Team | Data Quality | , , ,

When should you introduce a new product line?

How much of your advertising budget should you earmark for social media?

Should you renew your contract with a vendor?

No organization keeps track of the number of decisions they take in a day. What’s common between 99% of these decisions is that they’re backed by data. Data is easy to collect but simply having a ton of data is no guarantee for good decisions.… Read More

Data Quality Dimensions Can Raise Practical Concerns

Blog Administrator | Analyzing Data, Analyzing Data Quality, Data Quality, Data Quality Assessment | , , , ,

By Elliot King

As everybody knows, data quality is usually measured along seven dimensions–the four Cs of completeness, coverage, consistency, and conformity plus timeliness, accuracy and duplication. And the general method to judge data quality is to establish a standard for each of these dimensions and measure how much of the data meets these standards.

For example, how many records are complete; that is, how many of your records contain all of the essential information that the standard you established requires them to hold?… Read More

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