Is your data quality strategy continually evolving?

One of the significant problems data quality leaders face is changing people's perception of data quality. For example, one common misconception is that data quality represents just another data processing activity. If you have a data warehouse, you will almost certainly have some form of data processing in the form […]

Post a Comment

Dynamic data and coalescing quality

In my last post, I pointed out that we data quality practitioners want to apply data quality assertions to data instances to validate data in process, but the dynamic nature of data must be contrasted with our assumptions about how quality measures are applied to static records. In practice, the […]

Post a Comment

Five data quality archetypes, part 2

@philsimon on the need to recognize DQ differences.

Post a Comment

Forming data quality habits in 2015

It’s common at the start of a new year to create a long list of resolutions that we hope to achieve. The reality, of course, is by February those resolutions will likely be a distant memory. The key to making any resolution stick is to start small. Create one small […]

Post a Comment

Static Models and Dynamic Data

After working in the data quality industry for a number of years, I have realized that most practitioners tend to have a rather rigid perception of the assertions about the quality of data. Either a data set conforms to the set of data quality criteria and is deemed to be acceptable […]

Post a Comment

Big data preparation, big data quality and big data governance, oh my!

This isn't Kansas anymore. Oz has become a sprawling, smart metropolis filled with sensor data. How do we make sense of, clean, govern and glean value from this big data so we can get Dorothy home? The answer is SAS Data Management. With the latest portfolio updates, customers will be […]

Post a Comment

Crowdsourcing data improvement: Part 1

James Surowiecki wrote a book about The Wisdom of Crowds. Jeff Howe, who co-coined the term crowdsourcing, wrote a book about Why the Power of the Crowd Is Driving the Future of Business. In this blog series, I explore if it’s wise to crowdsource data improvement, and if the power of the crowd can […]

Post a Comment

Five data quality archetypes: Part 1

.@philsimon on the different folks you'll encounter in many large organizations.

Post a Comment

A few New Year’s data resolutions

Since now is the time when we reflect on the past year and make resolutions for next year, in this post I reflect on my Data Roundtable posts from the past year and use them to offer a few New Year’s data resolutions for you and your organization to consider in […]

Post a Comment

Why master data management is more than just data quality

I have participated in many discussions about master data management (MDM) being “just” about improving the quality of master data. Although master data management includes the discipline of data quality, it has a much broader scope. MDM introduces a new approach for managing data that isn't in scope of traditional data quality […]

Post a Comment