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20 Encounters of the Information Management Kind – #6 Converting History!...
There are two cases, that I can think of, where you may have to consider whether to convert history in a data warehouse. They are: 1. Initial creation of the data warehouse. In the past, we have always...
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Ideas for Addressing Customer Classification
Last time we started to look at methods used in setting product prices, and I asked whether knowledge of customer type would contribute to the determination of a “fair” price for an item that might...
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An Issue with Reporting Data Quality Issues
An organization’s perspective on data quality is often revealed by its data auditing practices. Some organizations practice data quality ignorance by not performing data audits, assuming that if they...
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Interviews, HR and Hiring Data Scientists
What makes a great data scientist? It’s an interesting question and, to be sure, an increasingly important one now that that we’ve entered the era of Big Data. On his blog, Andrew Dempsey lists three...
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How Can You Ensure the Readiness of Your Data During Data Migration?
Are you embarking on a data migration in the near future? If so, there is one nagging question that will loom across every stage leading up to the final moment of truth as your data finally lands in...
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20 Encounters of the Information Management Kind – #7 Data Conversion...
I don’t believe you can commit to the success of a data conversion without addressing quality (or lack thereof). Do you agree? If so, then why are there so many conversion projects that just move data...
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Customer Analytics: Classification vs. Segmentation
Last time we looked at a starting point for a classification model for determining the “goodness” of customers, based on some selected dimensions of value, measures, weights, scores and classification...
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The Eighth Law of Data Quality
The First Law of Data Quality explained the importance of understanding your data usage, which is essential to the proper preparation required before launching your data quality initiative. The Second...
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Data: The Ultimate Competitive Advantage
While we’re hearing more and more about the term, Big Data didn’t happen overnight. The data deluge could not have happened without the following taking place: Mobility Broadband Cloud computing and...
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Tackling Data Quality Overwhelm Head On
When starting out with data quality management, particularly if data quality technology is giving you a helping hand, it’s sometimes easy to become overwhelmed by the sheer volume of issues that your...
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Monitoring Data Quality a Little Too Continuously
In Nudge: Improving Decisions About Health, Wealth, and Happiness, Richard Thaler and Cass Sunstein explained how day traders with constant access to information about the value of their investments...
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Putting a Price on the Value of Poor Quality Data
When you start out learning about data quality management, you invariably have to get your head around the cost impact of bad data. One of the most common scenarios is the mail order catalogue business...
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20 Encounters of the Information Management Kind – What Does NULL Really Mean?
When I ask what a null value in the data means to your business, I get multiple answers. Some say, mathematically, it means zero. Well, if I’m doing an average I may not want to count that zero if it...
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Naming Conventions for Naming Things
In a recent email exchange with a colleague, I have been discussing two aspects of metadata: naming conventions and taxonomies. Just as a reminder, “taxonomy” refers to the practice of organization and...
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Big Data: Cui Bono?
Who benefits from Big Data? In his Thinkr series, author, photographer and technologist Rick Smolan asks many important questions about the era of Big Data. Consider a few from this recent video....
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Struggling with Sponsorship Apathy? Try Adopting Incremental Habits
Through the many interviews I’ve carried out with experts on Data Quality Pro, I’ve learned that the biggest data quality challenge is simply getting started. We all know that data is important. Even...
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20 Encounters of the Information Kind: Data Normalization – Third Normal Form...
I am not a purist when it comes to data modeling (logical and physical). This may be one of my flaws (there are so few – haha). I do believe that logical modeling and physical modeling are two...
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Names, Meanings, Context
Over the past few posts, I have been using a literary example from Through the Looking Glass to discuss concepts associated with semantics and taxonomies, and I am going to adapt the example somewhat...
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Midnight in a Sky above an Ocean of Aqua
More and more of our shopping these days is done online. Web commerce is booming, but some us are booing when the metadata describing the products we are shopping for is not easily discernible, causing...
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Big Data and Nomenclature Overload
I’m a big proponent of Big Data. I drink the Kool Aid. I’ve noticed something interesting over the past year, though. The number of data-specific terms has skyrocketed. Don’t believe me? Keep reading....
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