In my previous post, I looked into the magic mirrors of business leaders, more commonly called dashboards, as one example of how data visualization is used. In this post, I want to look at what we use to look — our eyes — and how they process whatever data we
There's an old statistical phenomenon which states that in listings of numeric data, the first digit of about 30% of the numeric values should start with the value of 1 (and ~17% should start with the number 2, 12.5% should start with the number 3, etc...). The phenomenon is known
David Loshin explains how to integrate MDM with your data warehouse.
I am asked quite frequently whether a company needs master data. Actually, I believe everyone has master data, it just depends on whether your company wants to manage their master data or not.
.@philsimon on the trickiest of definitions.
As Beth Schultz recently blogged, Data Visualizations Beg Your Attention. And as Noreen Seebacher recently blogged, A Picture Explains a Lot of Data. Although I agree with both concepts, and I recommend reading more than just the titles of those posts, I couldn’t help but wonder if what should be begging more
Yes, "Big Data is cool" but "all the cool kids are doing it" is no reason to forget about two of the most fundamental practices of data management: data archiving and data purging. Data management professionals need to work with their business and leaders to determine when data is no
David Loshin discusses master data model requirements.
Phil Simon (@philsimon) on the ubiquity of data.
In my previous post, I pondered how the inevitable lag time between the definition of requirements and the delivery of solutions is exacerbated by the business world fluctuating dramatically in short periods of time. Today’s business requirements may not only be different than yesterday’s business requirements, but today’s business requirements
