Too much push, not enough pull

As you might have noticed from my long absence in the blogosphere, I have been very busy managing and developing EMC Consulting's Data Quality Practice.  One thing has become very clear to me over the past few months ... data quality is an ambiguous term that means different things to different people.

I have also become aware of the fact that blogging lends itself to publishing a perspective, rather than collecting perspectives.

In an attempt to put some structure around the term data quality by collecting perspectives, I have decided to post some polls and then write about them.

I have chosen three rather basic polls in an attempt to build a baseline.  If you are reading this post, you are obviously interested in data quality (or an insomniac looking for a cure!).  Please participate in the polls and comment on this post if you feel I have missed a baseline measure that will help add clarity to data quality.

When is data quality useful?

[polldaddy poll=5684585]

When using data quality tools, what do you include?

[polldaddy poll=5684590]

Data Quality: underutilized or over-hyped?

[polldaddy poll=5684595]

Of course I have my own opinions, but I want this post, and the series of posts that follow, to be more about what others think than my own thoughts.

In an attempt to gather as many perspectives as possible, please pass this post around your network and feel free to add comments if you feel I have neglected to add something important.