DataFlux

How does one verify that the quality of data meets the business application’s expectations? Often, the concept of measurable data quality is foreign within an organization, with the notion of “bad data” being defined in terms of gut feelings. In reality, the more that data is shared, the more critical it is to clearly define what is acceptable in terms of meeting expectations. - Read the rest of this entry »

Everyone talks about massive amount of data that organizations have to handle these days. And there have been a number of estimates as to just how much data this is. One of the more interesting estimates comes from a study conducted at the University of California at Berkeley. According to the study, which was published in 2003, the world produced in 1999 something on the order of 1.5 exabytes of data, or 1.5 billion gigabytes. Professors Peter Lyman and Hal Varian, who conducted the study, state that this amount of data is equal to 250 megabytes of data for every single person on the globe (in 1999). The lion’s share of this data is digital data, which is growing according to some other estimates at 30 percent per year. - Read the rest of this entry »

I spend a lot of my time working with and around customer data. I write about it, do presentations about it, and most importantly, work with clients on how to plan, design, implement, architect, and educate their executives about it.

But when we peel back the layers of the customer databases we work with, there are likely to be more people in the database than just customers. - Read the rest of this entry »

I was recently approached by a colleague, an IT staff person, who told me that while he had been given the title of data steward, he mostly acted as a help desk operator. As the person tagged as being responsible for managing data quality issues, he had in fact become the person responsible for triaging data failures, determining what the issues were, and scrambling to borrow resources to help track down and correct the problem.

What struck me was… - Read the rest of this entry »

All companies have customers and suppliers. But the discrete relationships between a company, its customers and its suppliers are usually unique to its business. Those of us who have designed and built enterprise data warehouses already know that cookie cutter data models don’t reflect the specific and varied ways different companies do business. So presuming that an infrastructure solution like CDI can be built on a cookie-cutter, a fixed data model is equally impractical. - Read the rest of this entry »

The role of “Data Steward” is an interesting one, especially because of its complex duties and its mandate to play politics – politics in a good sense, if such a thing exists. - Read the rest of this entry »

Let’s see how we can exploit a business intelligence framework to improve data quality.

Here’s a question: to what degree are business intelligence initiatives used to monitor the performance of the operations used to populate the data warehouse that drives the business intelligence activity? - Read the rest of this entry »

Not long ago, I wrote an article on international data quality solutions. In it, I stated (in part): “The global marketplace presents a wealth of challenges for organizations of all stripes, and especially for those that are looking to capitalize on business that transcends political, cultural and, of course, physical boundaries.”

I know, I know, quoting oneself is the height of…well, hubris. But please be assured that I am not trying to hype myself, as it were, by leading with one of my own catchy phrases. I’m only trying to save myself a little time, and simultaneously make a valid point. - Read the rest of this entry »

There’s FUD around CDI. For those of you who aren’t software vendors, FUD means “fear, uncertainty and doubt.” Like all emerging technologies, CDI gets its FUD flung at it from stakeholders of the status quo. And the FUD-flinging’s begun! - Read the rest of this entry »

A while ago I provided a rather flippant answer to a reader who complained that I had given the “misleading impression that data quality is THE determinant of BI success.” I gave a rather flippant answer without, I suppose, addressing his concerns - which boiled down to, “BI is a mess because it is run by IT, its concepts are superficial and it isn’t relevant, in its current form, to about 95 percent of knowledge workers.” - Read the rest of this entry »