You don’t have to spend $$$$ to gain access to streaming analytics despite what the major providers might tell you. “Streaming analytics”, if you didn’t already know, is the latest buzz word in the “big data” world, and it usually comes with an impressive sticker price.

But what is Streaming Analytics and how does it fit into your data processing requirements? In principle we have three forms of dynamic analytics;

  1. Drip – data arrives in packets that might be big or small but the period between packets could be measured in days, weeks or even months. The analysis is performed as needed and typically the results go forward into a larger report, probably for a board level progress meeting, held two or three times per year.
  2. Trickle – data arrives in packets in regular time periods. The analysis is performed immediately and the results presented in a report soon thereafter. Typically, these results would go to the management team responsible for the operation of the study and we would be delivered weekly or monthly.
  3. Streaming – data arrives constantly, 24/7, and the analytics are calculated immediately and/or on demand. Results may be published to a report at defined intervals but essentially the operational team are able to monitor progress of the study ‘live’. Dashboards present information in an easy to digest form and overall control and monitoring can be given to those that need it, when they need it.

Galileo Analytics has been working in all three forms of dynamic analytics for some time. Our lead product – Galileo Cosmos™ – was designed from the outset to combine the core functionality that dynamic analytics required. When “Streaming Analytics” became a buzz word we realized that we already had the platform to deliver the functionality demanded.

To perform dynamic analytics, data must be cleaned, combined, and analysed as fast as possible. The process isn’t new, but today, with the increasing amounts of data we collect, the necessary speed is and to get this speed most providers ask you to pay more – especially if your need involves customization. Often, we are talking about a lot more.

With Galileo Cosmos™ we were able to leverage the required functionality and performance for Streaming Analytics from our existing codebase. The effect of this was to retain the flexibility of our approach and the visual impact of our delivery mechanisms and thereby reduce the cost to our clients of providing a true streaming solution.

So what are the key components?

  • Fast and flexible Data import
  • Ability to combine data from different sources
  • Rapid data cleaning and QA
  • Embedded analytics are completed as soon as the data are ingested, automatically
  • Output generated and transmitted in real time
  • Scalability to ensure that the data can never outgrow the capabilities of the system
  • Processing speed scales in line with the need meaning no delays for results

In addition, Galileo Cosmos™ contains the capability to enhance and enrich your healthcare data through a full suite of data exploration and analysis tools that were designed from the beginning to focus on the specific needs of healthcare.

Of course, in healthcare the need for genuinely real time streaming analysis is limited to applications where the data really are that fluid – sites where care is provided being the most important. In this situation streaming analytics can provide critical insights regarding developing risks (such as hospital acquired infections), evolving risks (such as readmission likelihood), or emergency management (resource allocation in the event of a large-scale emergency). In all these cases Galileo Cosmos™ can be employed.

Galileo Cosmos™ is a solution that offers all the benefits of streaming analytics without the kind of budget often associated with healthcare IT solutions.

Galileo Cosmos™ turns raw data into business insights in real time

Simon Fitall

About Simon Fitall

Simon is a knowledge engineer with 30 years experience in market research, data analytics and business intelligence within the pharmaceutical, biotechnology and medical device industries. With multiple patents in the field of advanced medical data analysis, Simon is an expert in data analysis with more than 20 years experience in working with, analyzing and creating models with patient data.

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