What does the future of analytics look like in your organizations enterprise architecture? Does it include thinking about a two speed approach to analytics which includes both: An agile rapidly changing analytics platform for innovation (a lab) seperated from operations and broad enterprise audience usage A slowly moving systematic enterprise analytics platform (a factory)
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Enterprise Stresstesting bedeutet die Abbildung zahlreicher Disziplinen: Datenmanagement, Modellierung, Szenariomanagment, Risiko Rechenkerne, Analyse- und Reportingumgebung. Jedes dieser Themen birgt in sich bereits eine gewisse Komplexität. Um sie zu integrieren, bedarf es einer übergeordneten Prozesssteuerung, die alle Fäden beisammen hält, die einzelnen Schritte koordiniert, dokumentiert und wiederholbar macht.
There is so much going on in our country right now socially, that I feel like someone has just placed a soapbox in front of me and dared me to climb up. Never one to resist, let's talk about parenting in shifting sands. Talking to your kids (of all ages) about
I’m not a big gambler, but there is something I would put my money on – analytics. Analytics is helping companies turn information into value. And yes, I mean money. If you want to learn about the latest analytics trends and get in on some of that “value” – attend
Big data. Streaming data. Complex data. We’ve all heard the reasons why organizations feel like they’re facing an insurmountable data challenge. Now, it’s time to do something about it. For the past few years, SAS has helped some of the world’s leading companies make sense of an avalanche of data.
My previous blog posts here for marketing have centred on data-driven marketing themes and how marketers can exploit data and analytics to create a more customer-centric, fact-based culture. And by extension, how this, combined with quality execution is likely to lead to better customer experiences and improved customer equity. This
Did you know that the education industry is heavily embracing data visualization to run their business? Just like any other industry, leaders in education need to understand their customers (i.e. students). They need to understand how the students are doing, how they're progressing and if intervention is needed to ensure
If you have not yet discovered the new Ask the Expert series on the SAS Training site, you are missing out on a treasure. Visit the site right now and review all of the available topics, from "Newbie" to Analytics to Visualization to good ol' SAS programming. Go on; I'll
¿Por qué conformarse con el almacenamiento de datos cuando se puede aprender a leerlos? Porque información no es igual que conocimiento, implementar una solución de visualización de datos analítica no tiene los mismos beneficios que contar con una simple visualización de datos. La visualización analítica de datos ayuda a detectar
Die Ausgangslage … … ist klar: historische Ereignisse führten immer wieder zu Extremsituationen, in denen Banken um ihre Zahlungsfähigkeit kämpfen mussten. Besonders hart traf es die Finanzbranche 2007 im Zuge der Immobilienkrise, die zu einer ausgewachsenen (Inter-) Bankenkrise und letztendlich sogar einen Staatenkrise führte. Ein Tail-Event in ausgereifter Form.
Have you heard of Meskimen’s Law? It states the following: “There’s never time to do it right, but there’s always time to do it over.” If you work in software development you’ve probably come across colleagues who seem too ready to apply this law in the realm of software quality.
➤ DISCLOSURE! In June 2018 Google introduced changes to the way it handles its Maps platform. They now require API key in order to embed a map, plus Google Maps "projects" must now be associated with a billing account. Unless these new Google rules are met, Google maps described in
Your customers are more demanding than ever before. Improving field quality and your customer's experience of your product is essential to staying competitive. However, truly understanding customer experience can be a daunting task. These recommendations have been refined and proven in dozens of manufacturers as simple ways to rapidly improve field quality performance. 1. Think big; start small.
You know that feeling when all your ducks appear to be in a row, all the numbers add up, all the boxes have been checked, but you’ve still got a sneaking suspicion that something is wrong? I’m not talking just gut feel here, more along the lines of, “The logic
I saw an interesting graph on dadaviz.com that claimed Italians had gone from drinking twice as much as Americans in 1970, to less than Americans in recent years. The data analyst in me just had to "independently verify" this factoid ... But before I get into the technical part of this
The cottage industry was based on workers buying raw materials, bringing them home and producing hand-crafted items to sell. The system worked, but was slow, tedious and expensive, producing goods that were affordable only by the rich. The Industrial Revolution changed all that. The factory system brought machines and workers
The XLSX libname engine in SAS allows you to read and write Microsoft Excel files in the same way that you can work with other data sets and databases. This article describes the basic (and some limitations) of the XLSX engine.
As discussed in the last BFD post, sometimes a difficult and expensive problem doesn't have to be solved -- it can simply be avoided. When the teetering boulder threatened the baby below the cliff, we removed the baby and no longer had to worry about propping up the boulder. When it
You are going to be spending proportionately more of your IT budget on security than you have previously spent or ever wanted to spend. Why? Because you and everyone else on this planet is engaged in the still early stages of an escalating information arms race, that, while you didn’t
Many of our authors often ask us where they can find real data that they can use without copyright or other confidentiality issues. Instructors too are always on the look-out for real-life data. Well, thanks to a new initiative supported by SAS, you can now access data from more than
@philsimon on the need to adopt new tools to understand events.
Less than a year ago, the country’s attention was on Dallas after the first Ebola patient died. Not only is that where this project begins, but also where it was presented at SAS Global Forum in Dallas. Sharat Dwibhasi and his classmates Dheerj Jami and Shivkanth Lanka from Oklahoma State
Hadoop, in-memory analytics, the Internet of Things (IoT), machine learning, data visualization— topics that are dominating the analytics airwaves. SAS is innovating in all these areas, rapidly developing new products and functionality to meet the needs of today’s analytic environment. During this year’s Technology Connection session, SAS Global Forum 2015
I read an interesting article recently that suggested analyst and data scientist job positions may be on the way out. The author argued that analytics are being incorporated more and more heavily into operational systems, making “analytic capabilities” more readily accessible to business users without the involvement of a data scientist. Being a data
SAS Event Stream Processing that is! The latest release of SAS Event Stream Processing will launch May 12, and numerous customers around the globe are already using it. So what’s the big deal? Why event streams are important to business SAS Event Stream Processing allows organizations to react to events
Pueden explorar los datos más rápido que una bala. Su forma de aprendizaje es más poderosa que una locomotora. Incluso pueden transformar miles de datos desordenados en información útil en un abrir y cerrar de ojos. Es realmente impresionante lo que pueden hacer… De hecho, muchas organizaciones están tratando de
The Institute of Business Forecasting's FVA blog series continued on March 2, with my interview of Steve Morlidge of CatchBull. Steve's research (and his articles in Foresight) have been a frequent subject of BFD blog posts over the last couple of years (e.g. The "Avoidability of Forecast Error (4 parts),
I've seen a lot of recent news articles purporting income inequality in the U.S. ("the rich get richer, and the poor get poorer") ... and I wondered if the graphs were a true/unbiased representation of the data. For example, I recently saw a couple of graphs in an article on the
A colleague and I were looking for a good example of how analysts used to use graphics to report data, a data visualization before and after, so to speak. We needed a good "before" screenshot for a “before and after” comparison for our SAS Global Forum 2015 paper, Visualizing Clinical Trial Data.
I recently spoke with John Cassara, a former U.S. Intelligence Officer and Treasury Special Agent, about the growing concern over trade-based money laundering (TBML) and how we can combat it. John retired after a 26-year career in the federal government intelligence and law enforcement communities. He's an expert in anti-money