Examining big data analytics for e-health, via Google PaaS

Recently I’ve been lucky to meet with the CTOs of two important Canadian public sector organizations, Canada Health Infoway and the Province of Ontario.

Indeed Dennis Giokas kindly presented on Cloud Computing in Healthcare at our recent seminar in Toronto.

This presentation was about the recent CHI Cloud white paper, which is quite visionary in its description of how Cloud will evolve and grow in E-Health.

In particular, and this was the common theme for Ontario as well, was the forecast of increasing use of SaaS (Software as a Service) as a delivery model.

This is a simple and logical part of the Cloud trend of course, but exciting to see it described in both strategy and real-world terms – The Province for example has recently a numbed of SaaS-specific tender RFPs.

E-Health Big Data PaaS

It’s exciting because both Dave and Dennis also describe it in terms of benefit to the local economy, and how this would be best served through new local SaaS ventures.

It is a better procurement model for many agencies and ideal for new and innovative software, like Open Data. This is an area packed full of opportunities for SaaS-savvy entrepreneurs.

Dave’s corporate strategist Samantha Liscio describes this in terms of this presentation: Open Data, Big Data – Open Data in Ontario.

This provides the overall strategic context for Open Data and Big Data – A combination that could be achieved through licencing, data production and then the use of that data somehow in a new social media context.

The Cloud model for then delivering this via a PaaS approach is described in the E-Health Cloud white paper. Specifically on page 25 they describe a need for Big Data Analytics, and also that it should be delivered via a PaaS – Platform as a Service.

Whether it’s called “predictive analytics,” “smart computing” or “analytics on cloud,” cloud computing and analytics provides a comprehensive offering of a combination of products that enable enterprises to move their business intelligence, data warehousing and online analytical processing (OLAP) workload to a cloud platform.

While the implementation of cloud analytics can take several forms at a high level, the following are parts of a cloud analytics platform that would be of interest to an enterprise:

- A virtualized infrastructure to support the basic cloud tenants to build a private/public/hybrid cloud

- PaaS in-line with the underlying cloud infrastructure that can support the analytical needs of reporting, analysis, dashboards, extraction, transformation and load (ETL) and predictive analytics

- Customized analytics applications in a PaaS/SaaS offering which are uniquely positioned for designing and developing customized analytics applications. The cloud provider is responsible for on-demand provisioning and the maintenance of software and hardware.

Standing on the Shoulders of Giants

How this can be leveraged for new SaaS ventures is described in a recent blog of mine, ‘Standing on the Shoulders of Giants‘.

So to answer the title of this article, we can see that these new SaaS ventures could be accelerated through the Google PaaS.

This can be explained through “Big Data Analytics for E-Health, via Google PaaS”, where we can identify a relevant Google PaaS service, Google Big Query, is a PaaS component that provides a Big Data capability.

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