TechCrunchIT reported today that a Rackspace data center went down for several hours during the evening due to a power grid failure. Because Rackspace is a managed service provider (MSP), the downtime affected several businesses hosted in the data center.
Over the past few months a flurry of announcements have begun swirling around the cloud computing space, which remains a nascent market in the overall IT realm. Do these announcements portend a fast maturity for the concept or just the typical "me too" that comes with a hyped market?
In June, RightScale, a cloud management software and consulting company that has become a bit of a poster child as a cloud integrator, announced a partnership with GigaSpaces that integrates their eXtreme Application Platform (XAP) clustering and cache solution with the RightScale automated cloud management platform for Amazon EC2 clients. The value of this partnership comes from the fact that EC2 simply provides you with a VM you can populate but no availability or scalability services. XAP is a cluster architecture that delivers these values and can be quickly and easily deployed via the RightScale tool.
Next came Elastra, a San Francisco startup building a Cloud Server, a middleware layer that turns a commodity infrastructure into a cloud (similar value to what 3Tera provides today). The first iteration deploys similarly to XAP -- as a software layer you load into EC2 VMs, that enables scale and availability to the apps you lay on top of it.
Earlier this week, if you happened to read any of my research on our site, you might have been scratching your head at my "new" photo, as seen below:
You might have asked yourself, "What has happened to one of my favorite Forrester analysts?" Was it the result of a) a face lift; b) gender reassignment surgery; c) successful prayers to the patron saint of the un-photogenic (when a good friend first saw my original photo last year, she asked in her typical blunt fashion, "Why do you look so puffy and awful?")
Certain words in the technology industry lexicon are so unspecific that they obscure more than they describe. Customization is one such word. Another is customer.
Who needs your products and services? Not General Motors. Not McGill University. Not the US Department of Labor. Instead, the collection of people, procedures, and problems that constitute a project define who the "customer" really is.
I learned the importance of this distinction by way of customer references. Everyone wants to have a Name Brand Customer as a reference. However, notoriety has nothing to do with customer success. A Big Name Manufacturer had less success, due to internal politics, than Dinky Manufacturer. Of course, dazzled with the glamour of working with Big Name Car Manufacturer, we wasted a lot of effort on trying to help people who, in all frankness, didn't really value our help, because they weren't ready to receive it.
When a new technology was introduced in the 1980's, my then Yankee Group boss Dale Kutnick would cryptically remark, "It's happening." But most of the "happening" was incremental, without much impact on society or culture.
25 years after "The computer moved in" (fascinating retrospective reading) all of that incremental digital change has accumulated. And the many water drops of progress have created a tidal force that, in its essence, is making things go away...
I’ve recently returned from SAS Institute’s Annual Analyst Event held June 23-24, 2008 in Monte Carlo. At this event, SAS leadership revealed a roadmap to amplify, with the most effective decision science yet developed, the judgment of professionals in a wide range of industries including retail and consumer goods. Forrester noted specific new science based processes, deployable without restrictions about legacy transaction applications for:
Merchandise planning. The most critical decision in any consumer goods value chain is which merchandise to stock. But this decision, although ultimately driven in retail by the buyer’s judgment, must draw on data and analytics that evaluate, based on historic demand) the relative likely revenue and margin resulting from different merchandise portfolios, and test the feasibility of the portfolios against constraints such as store space or labor availability or the firm’s available working capital.
Size optimization. For retailers selling footwear or apparel a statistical understanding of the distribution of sales by size by store is vital in order to meet consumers’ needs and avoid mark downs and stock outs. It’s well known that consumers’ sizes vary from one region or country to another, with Norwegians for example in general being taller for example than Greeks but retailers need powerful sparse data analytics to plan for the differences in populations that visit urban and out of town stores.
Space optimization. Retailers provide space in stores in proportion to their expect sales and margin for each merchandise item. But the complex tradeoffs between affinity items, with different margins and attracting different promotional funds simply demand an enterprise analytic approach rather than single user planning tools.
Readatwork is certainly one of the cleverest sites I've seen in a while. You can read a few short stories on line, in an interface that looks like the standard Windows desktop and PowerPoint. Now, it just needs more content.
In the beginning of the year, Harvard Business Publishing launched a collection of online simulations as part of its curriculum that expose learners to real business situations and enforce essential corporate skills. Learning simulations are interactive models of real-life processes, events, or interactions that have distinctive learning outcomes. Users can manipulate variables that change the state of the model — they can make mistakes, learn from them, and try again — emulating a real "learning by doing" approach. With these online simulations, learners can engage in common business situations within realistic scenarios, and learn how to fine-tune their communication, analytical, and decision-making skills.
The first simulation, Universal Rental Car is a pricing simulation focused on teaching employees pricing skills in a managerial environment, as learners take on the role of regional marketing manager at a rental car agency, and are tasked with pricing rental cars in cities across Florida. Sample the Universal Rental Car simulation (login = user, password = user) for three rounds, and explore the Prepare, Analyze, and Decide tabs.