I led an analytical culture track at the SAS Global Forum Executive Conference last month in Washington, DC. I talked with leaders in fields as diverse as healthcare, chemical manufacturing and government. Although these organizations have very different operating models, their challenges, comments and questions were similar. They all recognized
I was asked to speak recently on a topic that includes two hyped terms: Big data and sustainability. At the risk of igniting an anti-buzzword campaign, I added a third over-used term to that list: analytics. Even though individuals and companies use those three words – big data, sustainability, and
With as much as I travel, I have to confess that I’ve become a bit of a food snob. And for good reason, I might add. Two days in a Chilean hospital will make anyone stick with what they know and trust. After that experience, it was just me and
Last night, here in the U.S., an outbreak of deadly tornadoes tore across several states. Unfortunately, nobody knows how to predict a tornado with certainty, but let's brainstorm on how SAS Software can help analyze the data in the aftermath of a natural disaster like this... Being a graph guy, the first
Principle 4: Completeness – A bank should be able to capture and aggregate all material risk data across the banking group. Data should be available by business line, legal entity, asset type, industry, region and other groupings, as relevant for the risk in question, that permit identifying and reporting risk
Dear Rick, I am trying to create a numerical matrix with 100,000 rows and columns in PROC IML. I get the following error: (execution) Unable to allocate sufficient memory. Can IML allocate a matrix of this size? What is wrong? Several times a month I see a variation of this
What if virtual reality technology allowed you to immerse yourself in big data? That could be your future – and sooner than you think. It happened in August 2013 at the University of Washington: the first direct brain-to-brain communication, with one researcher controlling another researcher’s brain over Skype. Maybe in
¿Alguna vez ha imaginado una nave roja futurista que aterrizó en medio del desierto? Así es como se ve el mayor tejado de aluminio pre revestido del mundo: El parque temático cubierto Ferrari World en Abu Dabi, Emiratos Árabes Unidos. Ahora fíjese en la extraordinaria resistencia del color en este techo
As we saw last time with Steve Morlidge's analysis of the M3 data, forecasts produced by experts under controlled conditions with no difficult-to-forecast series still failed to beat a naive forecast 30% of the time. So how bad could it be for real-life practitioners forecasting real-life industrial data? In two words:
Over the past few months, many US states and districts have received data about student growth and teacher effectiveness. Some educators experience the excitement of outstanding scores and, most importantly, the success of their students’ growth. Some quietly plug along, satisfied to be meeting growth targets and deciding if it isn’t broken,
In our hyper-connected world, information technology plays a key role in nearly every field and industry. Higher education is no exception, and that’s where EDUCAUSE comes in. This non-profit association works to advance higher education through the use of information technology. One of the primary ways EDUCAUSE achieves its goal
The Spring 2014 issue of Foresight includes Steve Morlidge's latest article on the topic of forecastability and forecasting performance. He reports on sample data obtained from eight business operating in consumer (B2C) and industrial (B2B) markets. Before we look at these new results, let's review his previous arguments: 1. All
As an unabashed lover of data, I am thrilled to be living and working in our increasingly data-constructed world. One new type of data analysis eliciting strong emotional reactions these days is the sentiment analysis of the directly digitized feedback from customers provided via their online reviews, emails, voicemails, text messages and social networking
Just one last short article about properties of the Hilbert matrix. I've already blogged about how to construct a Hilbert matrix in the SAS/IML language and how to compute a formula for the determinant. One reason that the Hilbert matrix is a famous (some would say infamous!) example in numerical
As I was doing my taxes, I wondered where the government is spending my tax dollars. And being a SAS user, I decided to find out using a graph ... I did a few Google searches on "tax graphs" and found one on the CNN web site that I liked - it
I’ve been to a fair number of SAS User Group International (SUGI) and SAS Global Forum conferences over the years, but I don’t think I’ve been to one as productive, well-organized and fun as this year’s conference in Washington DC. Part of what made the conference very relevant for many
Analytics gives us not just the ability but the imperative to separate our planning activities into two distinct segments – detailed planning that leads to budgets in support of execution, and high-level, analytic-enabled business/scenario planning. My critique of Control Towers in this blog last time led me not only to
Principle 3: Accuracy and Integrity – A bank should be able to generate accurate and reliable risk data to meet normal and stress/crisis reporting accuracy requirements. Data should be aggregated on a largely automated basis so as to minimize the probability of errors. It seems logical that banks would want
I have previously written about the scope of local and global variables in the SAS/IML language. You might wonder whether SAS/IML modules can also have local scope. The answer is no. All SAS/IML modules are known globally and can be called by any other modules. Some object-oriented programming languages support
Here is editor Len Tashman's preview of the new Spring 2014 issue of Foresight. In particular note the new article by Steve Morlidge of CatchBull, reporting on an analysis of eight B2B and B2C companies, which we'll discuss in a separate post. An organization’s collaboration in forecasting and planning has
Para tener óptima administración comercial y captar nuevos clientes, las compañías de telecomunicaciones necesitan un amplio conocimiento de sus infraestructuras y sus consumidores.
When you run a program or task in SAS Enterprise Guide, the application wraps your job in an "ODS sandwich", the colloquial term we use for the ODS statements necessary to create output that can be viewed in your project. That's convenient for exploring and refining your program, but at
El gobierno de datos se ha convertido en un sello para todo lo que tiene que ver con los datos. De hecho, si busca el término en Google, encontrará referencias a la calidad de los datos, los metadatos, el almacenamiento de datos, la propiedad de los datos o la seguridad
Q: How would you set the target for demand planners: all products at 0.7? All at practical limit (0.5)? A: In principle, forecasts are capable of being brought to the practical limit of an RAE of 0.5. Whether it is sensible to attempt to do this for all products irrespective
Last week I described the Hilbert matrix of size n, which is a famous square matrix in numerical linear algebra. It is famous partially because its inverse and its determinant have explicit formulas (that is, we know them exactly), but mainly because the matrix is ill-conditioned for moderate values of
Q: How important is it to recognize real trend change in noisy data? A: It is very important. In fact the job of any forecast algorithm is to predict the signal – whether it is trending or not – and to ignore the noise. Unfortuantely this is not easy to
I'm in the grocery store with a "mental" list of 3 items to pick up: bread, eggs, and something unusual like cupcake liners. My phone rings. It's my wife (or sometimes a daughter) asking me to pick up one or two more things, maybe orange juice and bananas. Suddenly, the
Autor: Karim Tsouli, CIO und Mitglied des Vorstands bei der CreditPlus Bank AG „Wenn Daten nicht nur aus Gründen der Dokumentation erfasst werden, sondern diese als Basis von Geschäftsentscheidungen dienen, kann Business Intelligence (BI) helfen, eine zuverlässige Analyse bereitzustellen." Karim Tsouli, CIO CreditPlus Bank AG
Principle 2: Data architecture and IT infrastructure – A bank should design, build and maintain data architecture and IT infrastructure which fully supports its risk data aggregation capabilities and risk reporting practices not only in normal times but also during times of stress or crisis, while still meeting the other
Q: Do you think the forecaster should distribute forecast accuracy to stakeholders (e.g. to show how good/bad the forecast is) or do you think this will confuse stakeholders? A: This just depends what is meant by stakeholders. And what is meant by forecast accuracy. If stakeholders means those people who
