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Nearly every organization has to deal with big data, and that often means dealing with big data problems. For some organizations, especially government agencies, addressing these problems provides more than a competitive advantage, it helps them ensure public confidence in their work or meet standards mandated by law. In this
One of the key benefits of creating graphs using GTL or SG Procedures is their support of plot layering to create complex graphs and layouts. Most simple graphs can be created by a single plot statement like a Bar Chart. Complex graphs can be created by layering appropriate plot statements to
My last post described my top general business analytics books, those that would appeal to business leaders and analysts alike. This post is a bit more specific, and covers books that will help you to learn for yourself. It is therefore mainly aimed at analysts — but I still hope
When I was a kid, I always looked forward to Casey Kasem's American Top 40 song countdown at the end of the year. Did I listen to check whether my favorite songs had made the list, or to critique how well the people making the list had done in picking the 'right'
In my earlier post about WHERE and IF statements, I announced that the DATA step debugger has finally arrived in SAS Enterprise Guide. (I admit that I might have buried the lead in that post.) Let's use this post to talk about the new debugger and how it works. First,
Data virtualization is an agile way to provide virtual views of data from multiple sources without moving the data. Think of data virtualization as an another arrow in your quiver in terms of how you approach combining data from different sources to augment your existing Extract, Transform and Load ETL batch
En todos lados se habla de lo mismo: transformación digital. Es generalizada la necesidad de hacer las cosas diferentes, ya sea por medio de una nueva apuesta o reinventando la forma en la que hoy se hacen las cosas. Tener acceso a soluciones en todas partes gracias a la Nube
Balance. This is the challenge facing any organisation wishing to exploit their customer data in the digital age. On one side we have the potential for a massive explosion of customer data. We can collect real-time social media data, machine data, behavioural data and of course our traditional master and
Mal ehrlich, wenn ich Sie fragen würde, worüber die Kandidaten im diesjährigen US-Wahlkampf in ihren Aufeinandertreffen debattiert haben – welche Kernthemen würden Sie mir spontan (abseits von Skandalen und Affären) nennen? Und könnten Sie diese Kernthemen den einzelnen Kandidaten zuordnen? Als ich mir diese Frage stellte, war die Antwort –
My preference, of course, would be for everyone to get all the nutrients their body needs for optimal health from the food they eat. In this day and age, however, that is getting harder and harder to do for many reasons…
In honor of today’s #GivingTuesday, which "harnesses the potential of social media and the generosity of people around the world to bring about real change in their communities,” I’ve been thinking about what constitutes “real change” and the role analytics can play on the many social issues our planet faces.
“Omg, Mom, people are going to think you actually look like that!” My 16 y/o recently got a Facebook account (apparently passé for teens in US but not in Europe and as her circle expands…). So, now she has a front row seat to my (apparently embarrassing) selfies. It’s
est plus près de la maison, está más cerca de casa, está mais perto de casa, dichter bij huis, is closer to home, eh! In analytics and statistics, we often talk about sample sizes. The size of the data sets that you analyze are a measure of the amount of
Has anyone ever broken up with you, and left you thinking "Wow, I didn't see that coming!" In hindsight, maybe you could have seen it coming. At least from a statistical perspective. Let's dive into this topic with some lighthearted discussion, and plot some Facebook data... When it comes to
One aspect of high-quality information is consistency. We often think about consistency in terms of consistent values. A large portion of the effort expended on “data quality dimensions” essentially focuses on data value consistency. For example, when we describe accuracy, what we often mean is consistency with a defined source