In the big data era, I hear a lot about new and dynamic data sources that are giving companies a wide range of opportunities – and anxiety. When industry wonks talk about the “speeds and feeds” inherent in big data, they are often talking about an avalanche of transactional or
It's hard to imagine a hotter job now than the data scientist. Supply trails demand and, as a result, there's no shortage of myths around them. But is there any real difference between traditional statisticians and what we now call data scientists? I asked my friend Melinda Thielbar, a research statistician developer at JMP (a
While big data is rife with potential, as Larry Greenemeier explained in his recent Scientific American blog post Why Big Data Isn’t Necessarily Better Data, context is often lacking when data is pulled from disparate sources, leading to questionable conclusions. His blog post examined the difficulties that Google Flu Trends
Last time we discussed two different models for syndicating master data. One model was replicating copies of the master data and pushing them out to the consuming applications, while the other was creating a virtual layer on top of the master data in its repository and funneling access through a
For most organisations, issue management is seen as an administrative chore. Scattered across the organisation, data workers diligently resolve issues often via their own local issue management process. With silos of data comes silos of maintenance, and this is a real shame because the data these systems possess is a
How does one select the "right" or "best" way to visually represent data? Of course, the short answer is it depends. (In fact, that theoretical manner might not even exist.) Beyond that, it's an interesting question and, as I argue in The Visual Organization, a harder one to answer these days
Teller, the normally silent half of the magician duo Penn & Teller, revealed some of magic’s secrets in a Smithsonian Magazine article about how magicians manipulate the human mind. Given the big data-fueled potential of data science to manipulate our decision-making, we should listen to what Teller has to tell
In the past few posts we examined opportunities for designing a service layer for master data. The last note looked at the interfacing requirements between the master layer and the applications lying above it in the technology stack. Exposing accessibility to master data through the services approach opens new vistas
Some of the most common reasons for defective data come down to a simple lack of coordination between the various groups involved with preserving the integrity of data logic, content, structure and assurance. By improving this process of coordination between the different silos, you can dramatically improve the quality and governance
Upselling isn't exactly a new creation of capitalism. Whether it's extended warranties at Best Buy or your credit card company offering you some type of enhanced protection when you dial the call center to investigate a charge, most of us have had the experience at one time or another. Consider
