Whenever there is a limited supply of anything we always try to find ways to more efficiently manage it. This is true whether the conversation is about natural resources or something more esoteric as business analytics.
The fact remains that there is a general shortage of trained business analysts in the world. This shortage is creating new opportunities to deliver analytics-as-a-service in much the same way that companies routinely access customer relationship management (CRM) software.
The challenge, however, has been that the cost of the IT horsepower needed to deliver analytics-as-a-service was beyond the means of most companies that have large amounts of data worth analyzing. But now that we're starting to see the emergence of next-generation in-memory server architectures, the feasibility of analytics-as-a-service starts to become much more apparent.
For example, Glen de Vries, president of Medidata Solutions Worldwide, a provider of software-as-a-service (SaaS) applications, expects to make use of the SAP High-Performance Analytics Appliance (HANA) architecture to deliver analytics in real time as a standard part of the company's suite of applications. That analysis will not only be based on specific customer data, but will also be able to identify trends in aggregate. That, says de Vries, means that Medidata will be able to tell customers how any given clinical trial compares to a range of similar clinical trials in real time.
IT organizations have been collecting large amounts of data for years, the bulk of which is useless because there was no real way to cost-effectively get at it. But as in-memory computing evolves alongside new constructs such as Hadoop for cost-effectively managing large amounts of data, the ability to routinely deliver analytics-as-a-service in real time across a range of vertical industries will soon be upon us.