Big data. No, that’s not quite big enough. Let’s adjust the reverb on the mic a bit… ahem: BIG DATA-A-A-A-A. There’s quite a bit of buzz these days about Big Data -some might argue it’s just buzz- but there’s relevant substance to the concept and intriguing propositions for the future. But what exactly constitutes Big Data? Big Data is in some ways a transient side effect of the information age – as the amount of data we accumulate, process, transmit, and store exponentially grows, the totality of said data has exceeded our capacity to conventionally manage it. The great invention of the information age: the almighty Relational Database Management System (RDBMS) is ill equipped to contend with Big Data. Databases store structured relational information in a centralized repository or a highly ordered federation of repositories. As the size of the dataset expands, so too must the size and power behind the database. Naturally, once the data exceeds a certain amazing colossal size, the corresponding database required to conventionally manage such a dataset exceeds reasonable practicality. Furthermore, as the diversity of the data increases, and the speed at which it is collected accelerates, any measure of structure becomes impossible. Even our favorite positronic golden boy is left scratching his head in bewilderment. The technology and innovation surrounding Big Data is very much about solving this particular problem. So how is this going to help us reroute power from the phaser banks to the starboard cappuccino machine? More importantly, what does Big Data have in store for engineering and, more specifically, Product Lifecycle Management (PLM)?
Fasten all seatbelts, seal all entrances and exits, close all shops in the mall, cancel the tree ring circus, secure all animals in the zoo, prepare the ship for… an upgrade. Software upgrades should be a time of unbridled anticipation, celebration, and joy; after all upgrades bring new features, performance enhancements, improved interfaces, and don’t forget about all that bug squashing. Why then, in the world of Computer Aided Design (CAD) are upgrades met with such trepidation? More importantly, as cloud technologies continue to permeate the tools of engineering design, and the Software as a Service (SaaS) model becomes more commonplace, what does the future hold? Continuous upgradability is often quoted as one of the primary advantages of SaaS, supplanting the traditional model where upgrades must be purchased outright. Is this a welcome development, or is it time to push the self-destruct button?
No doubt the accelerating drumbeat of technological innovation is imposing economic, social, cultural, and emotional effects on the human condition across all boundaries of geography, industry, and expertise. Engineering and manufacturing are no exception to this relentless technological tide. Both are undergoing a transformation that may be as profound and broadly evolutionary as the Industrial Revolution if not more so. What drives this acceleration? All invention and discovery is drawn in part by standing on the work of those came before. But as the breadth and depth of that knowledge increases, and the utilization of it similarly scales, we’re faced with an exponential curve of innovation and discovery. Consequently that also means a metric crapload of change. It can be exhilarating; it can be depressing. That precise dilemma has been a primary motivator as to why I write in this space at all – understanding what this means for engineering in general is crucial for the future. But before we get all wrapped up in singularity monsters that look like Caribbean pirates, the end of economic scarcity, or whether the guy who just handed you a Frappucino is really a Cylon, let’s take a step back. Way back. Let’s go back in time, through the ages of time and space… all the way back to last month.
Last time on E(E) in Part 1 of Cloudfusion, we outlined how the ongoing cloud bombardment is certainly creating plenty of disruption and confusion in the Computer Aided Design (CAD) market. If you missed Part 1, catch yourself up right here. Tired of the word cloud already? You’ll have to endure a few more invocations, I’m afraid. In an attempt to diffuse the ongoing cloudfusion, we’ll dive right into defining the various cloud technologies that are relevant for CAD. Here we go. In no particular order:
Cloud this. Cloud that. Cloud applications, cloud delivery, cloud sharing, cloud processing, cloud in your pocket, cloud at your company, cloud in your breakfast cereal. These days the momentum of The Amazon Cloud is overwhelming. Yet, the avalanche of cloud solutions is only just beginning for Computer Aided Design (CAD). The wide range of future possibilities have some people very, very excited. Others are not quite so keen to cheer, concerned about intellectual property protection and costly licensing models, among other conundrums about control, ownership, and obsolescence. Despite all the excitement and dread, there’s a more prevalent reaction that overwhelms both the enthusiastic early adopters and the despondent naysayers: confusion. With the relentless bombardment of cloud marketing for just about everything, it’s easy to mistake the cloud as one monolithic approach. There’s a horrendous amount of confusion that everything deemed cloud must necessarily be a subscription based, remotely-hosted, platform independent, socially collaborative, virtualized elastic computing platform dependent on the internet. It’s all cloud, right? Cloud, cloud, cloud. Just say cloud one more time. I double dare you.