May 03, 2013 by Dylan Jones
Although I do far less on-the-ground consulting than I used to, I still occasionally get to sample the delights of walking into an organisation, performing a data quality assessment and watching the occasional jaw hit the table when the client sees the actual state of their data.
May 02, 2013 by Phil Simon
Can an organization that has historically managed its data poorly start “doing” Big Data well? It’s an interesting question, and I’m not the only one asking it.
May 01, 2013 by Jim Harris
In previous posts, I explained how measuring is intrinsically fuzzy and what is being measured is intrinsically fuzzy. In this post, I want to take on the common adage: “you can’t manage what you can’t measure.”
Apr 30, 2013 by David Loshin
Last time we looked at how the tools and methods incorporated within a master data management system can contribute to ensuring the satisfaction of the success criteria for data warehouse consolidation. MDM provides some valuable capabilities that will simplify the consolidation processes.
Apr 26, 2013 by Dylan Jones
When we design systems, there is always a desire to build something that will support the business for some considerable time. A lot of banks, for example, still run on mainframe systems that have banking software that goes back literally decades.
Apr 25, 2013 by Phil Simon
I have a love-hate relationship with Twitter. I love the spontaneity of it all and the ability to connect with new folks. On the other hand, though, it’s exceedingly difficult to summarize a cogent argument in only 140 characters.
Apr 24, 2013 by Jim Harris
In a previous post about data visualization, I discussed how our expectations can distort the data we visualize a lot more than we may realize, causing us to mistake dashboards for magic mirrors reflecting back our own image of what we want our data to show us.
Apr 23, 2013 by David Loshin
In the past few postings we looked at some of the issues that emerge as a result of uncontrolled creation of data warehouses and data marts. I suggested that the goals of a data warehouse consolidation project should not only include the creation of a new data asset that accommodates the users of the “to-be-consolidated” warehouses and marts, but that those systems should be retired and replaced by the new asset.
Apr 19, 2013 by Dylan Jones
How do you become a better data quality professional? I get asked this question a lot and it’s often by those who are looking to learn new skills in technology, tactics and methodologies for data quality.