Data warehouse (DWH) environments have typically been the standard when it comes to supporting analytical environments. There can be many systems supporting a particular modeling or analytical group, and because these groups have varying requirements for data, the replicated data is maintained because the transition to new storage and computing
Few companies had histories as storied as Eastman Kodak. Although the company developed the first digital camera in 1975, "the product was dropped for fear it would threaten Kodak's photographic film business." [Wikipedia] Well, we all know how that turned out. In September, the company emerged from bankruptcy, but its future is anything
I have previously blogged about sneezing to unleash the data quality ideavirus, but in this post I have a different kind of sneezing in mind and, unfortunately, in nose. The common cold is so-called because it’s the most common human infectious disease. Despite the apparent irony of my traditional spring and summer
In the past few weeks I have presented training sessions on data governance, master data management, data quality and analytics at three different venues. At each one of these events, during one of the breaks a variety of people in my course noted that the technical concepts of implementing programs
Rafael Nadal is nothing less than a freak of nature on the tennis court. One oft-cited stat among tennis aficionados: Nadal routinely hits the ball at 5,000 revolutions per minute. By way of contrast, Roger Federer's strokes come in at 3,200 RPM. Put differently, "Rafa" hits the ball with 50 percent more
Design of the data warehouse for staging, the lowest level of granularity (history), and the data marts has to be tuned based on how these levels are used. Let’s evaluate some characteristics about each level. STAGING – Staging areas are used as a place to land data for propagation and integration
In my previous post, I outlined the main components needed for a phased approach to MDM. Now, let's talk about some of the other issues around approaching MDM: data governance and the move to enterprise MDM. Where does governance come in? Throughout your MDM program, it's important that deep expertise
I’m continuing my series on practical techniques that anyone can use to leverage data quality for bottom-line gains. Last week I talked about the link between data quality and service consistency, giving you some tips on how to improve both. This week I want to talk about a simple technique
As I responded to the final edits on The Visual Organization, I couldn't help but reflect a bit. We've come so far since the 1990s with primitive Excel bar and pie charts. Now more than ever, it's easy to create visually compelling graphics that tell a story. Heat maps, tree maps, choropleths
In my previous post, I talked about planning your MDM initiative and the importance of data quality and data governance to the effort. Today, we're going to drill in a bit into Master Data Management Foundations, a SAS offering unique in the marketplace that serves as a bridge between data
