Mensen, die door een dwarslaesie gebonden zijn aan een rolstoel, weer laten opstaan en lopen met behulp van technologische ondersteuning. Dat is het doel waar Project MARCH zich voor inzet. Het team, bestaande uit 26 studenten van o.a. de Technische Universiteit Delft en Haagse Hoogeschool, zetten een jaar lang hun
Tag: event stream processing
Almost everyone enjoys a good glass of wine after a long day, but did you ever stop to wonder how the exact bottle you're looking for makes its way to the grocery store shelf? Analytics has a lot to do with it, as SAS demonstrated to attendees at the National
I suffer from arthritis. You can tell just by watching me walk: Depending on the day, I have a slight limp, which varies in severity based on a number of factors such as the time of day and recent physical activity. Years of treatment for my condition have shown me
This series of videos spotlights a very powerful API that lets you use Python while also having access to the power of SAS Deep Learning.
Analytics braucht große Ressourcen? Das muss nicht sein. Und es darf auch nicht sein, wenn es um die Auswertung von Daten direkt an dem Ort, an dem sie entstehen, geht. Autonome Fahrzeuge, Fräsmaschinen oder Sensoren in Fußballschuhen sind nur einige Beispiele, wo „Edge Analytics“ benötigt wird, um eine „Funktion 2.0“
When you hear someone refer to an ‘inside baseball’ move, it means they’re playing into the subtleties of the game. Inside baseball requires a high level of awareness, experience, and strategic thought. This typically results in a mix of strategies to get runners on base and manufacture runs rather than
David Loshin provides an alternate take on streaming data in the context of legacy systems.
I have lived in the Town of Cary for more than twenty years; two of my three children were born at the local WakeMed Cary Hospital. I’m a big fan of my city, or town as it prefers to be called – even though the population is over 160,000. That’s
A future of flying cars and Minority Report-styled predictive dashboards may still be some time away, but the possibilities of robotics and Artificial Intelligence (AI)-powered automation are a reality today. From connected cars to smart homes and offices, we see daily how big data and the Internet of Things (IoT)
“Quick response forecasting (QRF) techniques are forecasting processes that can incorporate information quickly enough to act upon by agile supply chains” explained Dr. Larry Lapide, in a recent Journal of Business Forecasting column. The concept of QRF is based on updating demand forecasts to reflect real and rapid changes in demand, both
If you’ve been waiting for the buzz to settle around the Internet of Things before deciding how to invest in this new technology space, now’s the time to stop waiting. I’ve been working in the technology sector for a few decades, and the innovation and excitement I’m seeing around IoT
Will the IoT live up to the hype? Yes. A most resounding YES. In fact, it will exceed the hype, because we don't even know all the IoT possibilities yet. We don’t know what we don’t know, and that lack of imagination limits even our hype. Where we are with
For many industries, products and features are no longer the most crucial differentiators in the minds of customers. Take mobile telecommunications, for example. The recent market shift from virtually no unlimited data plans to announcements of unlimited data offerings by every major US wireless carrier in a short span of
Let me start by posing a question: "Are you forecasting at the edge to anticipate what consumers want or need before they know it?" Not just forecasting based on past demand behavior, but using real-time information as it is streaming in from connected devices on the Internet of Things (IoT).
„Durchsatz ist wichtig, jaja“, Supply-Chain-Leiter Herr Aklit lehnt sich zurück, faltet seine Hände über dem üppigen Bauch und sagt zu Lenin: „Sie haben ja schon einiges in Fluss gebracht mit Ihren Projekten zur Datenanalyse im Internet of Things.“ Er atmet tief durch und schaut aus dem Fenster: „Alles fließt …“,
Jim Harris discusses how the lines between data management and analytics are fading.
Lenin und ich sitzen im Publikum und applaudieren heftig: Seine Chefin hat ihren Vortrag beendet über „Datenqualität als Erfolgsfaktor im Internet of Things“. „Kein Datenqualitätsprojekt ohne Hilfe von oben“, raunt Lenin mir zu, "Unterstützung vom Boss ist manchmal wichtiger als tolle Software." Ich will beleidigt darauf hinweisen, dass seine Chefin
@philsimon says that old stalwarts sometimes just don't cut it.
David Loshin extends his exploration of ethical issues surrounding automated systems and event stream processing to encompass data quality and risk considerations.
Unless you’ve been living under a rock, you've surely noticed the increasing numbers of headlines about big data, Hadoop, internet of things (IoT) and, of course, data streaming. For many companies, this next generation of data management is clearly marked "to play with later." That's because adopting the next wave
I’m drawn to immersive analytics (IA) because it covers areas I’ve been looking at since 2012, and have been publishing on since early 2014, like virtual reality and data worlds. I’m retroactively applying the cool new term IA (not to be confused with AI for artificial intelligence) to all of my activities
We've all seen it before – a truck on the side of the road with the hood up and the driver desperate to figure out what’s wrong. In this situation, not only is a customer not receiving goods on time, but the problem is exacerbated by the fact that most
Streaming technologies have been around for years, but as Felix Liao recently blogged, the numbers and types of use cases that can take advantage of these technologies have now increased exponentially. I've blogged about why streaming is the most effective way to handle the volume, variety and velocity of big data. That's