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The Transformative Power of Data and Workflow Automation
The printing press, invented in Europe around 1440 CE, was for roughly the next 500 years the primary means of generating and storing data. However, since the advent of computers in the mid-1990s (depending on which model you consider the “first”), we’ve seen an attendant explosion of data, which is only accelerating.
Moore’s Law projected the number of transistors that can fit on an integrated circuit would double roughly every two years—which has proven particularly accurate. Remarkably, the rate at which data are being generated is even faster than Moore’s Law. However, the combination of 3 billion people on the Internet with mobile apps and sensors in an increasing number of smart devices is a recipe for an exponential increase in data which computers will have a hard time keeping up with—not only from a storage standpoint, but also a processing standpoint. The need to find ways to harness, understand and use data will ultimately transform the way we work.
As one would expect, this massive growth in data has created waves of downstream demand—for storage capacity as well as for analytical tools to make use of it. We will continue generating data (likely at an accelerating rate), but absent means of adequately storing it accessibly and in such a way that it can be called up more or less instantaneously and analyzed in whatever context is relevant, it is relatively less useful.
As computers have evolved, so have storage solutions. Among the relatively early shifts was to a cloud-computing model, which allowed businesses (and individuals) to take advantage of computing services, including servers, storage, databases, networking, and so on, without necessarily hosting all of the accompanying infrastructure onsite. This proved a meaningful source of cost-savings for companies which now need less space (for servers) and can operate with a smaller and more focused IT staff. Further, they no longer need to own the hardware, software and other infrastructure necessary to run their businesses.
Nearing a decade into broad adoption, companies are increasingly transferring their data into the cloud—in turn introducing new possibilities and challenges alike. For example, how do individual users access company data? Who has access to which data? How should these data be managed, stored, archived, analyzed, etc.? And there are ancillary questions that arise, too: What software solutions best allow analysis of these data? How should the data be secured—particularly in highly regulated industries (such as finance, health care, defense and others) in which data security concerns are paramount? We believe answering these questions will prove fruitful for well-positioned technology companies well into the future.
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