In a previous blog I discussed the four primary MDM architectural styles: consolidated, registry, coexistence, and transactional. In case you missed it, read it here: MDM Architecture Styles – Do you have the right mix? Each has their individual strengths and weaknesses, but no single MDM architectural style is ideal for every application.
Author Archive for: brian.jones
About Brian Jones
This author has yet to write their bio.Meanwhile lets just say that we are proud Brian Jones contributed a whooping 8 entries.
Entries by Brian Jones
Velocity is perhaps the most important concept in agile development. In his recent Agile 101 class at the TDWI BI Summit in San Diego, Ralph Hughes defined velocity as “The number of story points that can be delivered comfortably in an iteration.” That estimate effects many other estimates, such as the size and mix of […]
The first twenty-plus years of data warehouse projects yielded failure rates above fifty percent, and the waterfall methodology took much of the blame. Ironically, as Ralph Hughes points out in his book Agile Data Warehousing Project Management, the waterfall methodology itself was based on a “grievous misreading” of another work. Dr. Royce’s 1970 white paper […]
This seems so obvious that it hardly warrants mentioning, right? So why have I visited so many companies over my career where data marts, or even entire warehouses, were built using reference data from multiple sources where the data integration is ad-hoc and hardwired?
Like many baseball fans, I was spellbound by Moneyball, the 2003 Michael Lewis book that told the story of how Oakland Athletics general manager Billy Beane and his staff leveled the playing field between baseball’s biggest teams and his small market club by finding overlooked value in the “big data” of baseball statistics.
The analytic sandbox, also called a data sandbox, is an idea that resurfaced in a big way in 2012. In case you haven’t come across one yet, Techopedia defines the data sandbox as “a scalable and developmental platform used to explore an organization’s rich information sets through interaction and collaboration.”
When recently pondering how balance data should be modeled, I was reminded of my favorite Star Trek episode, The Balance of Terror. Those sneaky Romulans had crossed the neutral zone and were destroying Federation outposts. Naturally, only the Enterprise was close enough to intervene.
Since the beginning of data warehousing, practitioners have been comforted to know that facts—the individual business events that are quantified and measured—don’t change once recorded. That’s generally true when your warehouse is fed from a few highly reliable sources like the enterprise ERP and CRM systems; however, many warehouses rely on data sets that originate […]