This is the time of year when we like to make predictions about the upcoming year. Although I am optimistic about the potential of predictive analytics in the era of big data, I am also realistic about the nature of predictability regardless of how much data is used. For example, in
In my last post I introduced the term “behavior architecture,” and this time I would like to explore what that concept means. One approach is to start with the basics: given a business process with a set of decision points and a number of participants, the behavior architecture is the
The "Internet of Things" is the latest buzzword characterizing the machine-generated big data that has outstripped our ability to derive value from it. Think of UPS delivering 16 million packages every day through various hubs and all the logistics and decisioning that goes into that. But how does an organization
I work with some fabulous people! They are team players, motivated and ready to take on the world. These are the Millennial Generation or Generation Y. These people were born in the technology age and expect data to be at their fingertips, which gives information technology (IT) a bit of heartburn when it comes
My new favorite game is quite addictive, simple and, believe it or not, free. I call it "Stumped by Google Autocomplete." Here's how it works: type any word or phrase into Google, and see what Google suggests with it's Autocomplete function. Like all things Google, this feature learns from searches
I want to create a new series on The Data Roundtable that focuses on providing practical tips for improving data quality. Consistency is a key dimension often referred to in data quality practitioner circles. This refers to a rule where data must be consistent between two locations. For example, if
When you hear the term “business rules,” what comes to mind? Some examples would be constraints in a query, a data mapping, a data quality constraint, a data transformation, a model or an algebraic equation. It can also be a policy that must be enforced as part of a business
Netflix has been on quite the run over the last year. Its stock has exploded as its customer base nears 40 million. What's more, the company has positioned itself well with highly regarded original content and a strong foothold in the streaming business. Despite its success, complacent is not a
For decades, data quality experts have been telling us poor quality is bad for our data, bad for our decisions, bad for our business and just plain all around bad, bad, bad – did I already mention it’s bad? So why does poor data quality continue to exist and persist?
The challenge of data/information management practitioners attempting to initiate an analytics program intended to benefit a target audience is that after the analysis is completed, there is no control over how the results are used, or if those results are used at all. In my last post, we considered modeling
