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Data at Rest vs in Motion: It’s Not an Either-Or Choice
August 25, 2020 Blog

 

In life or death situations, every second counts.

Let’s say a nurse noticed an irregularity to a patient’s vital signs, such as body temperature and pulse rate at 1 AM. However, the patient lives far away from the hospital and the data that the nurse obtained was actually generated an hour ago due to the limitations of the tools and devices used. By the time the hospital sends an emergency team, the patient could already be in a critical condition.

If the healthcare facility were able to monitor patients in real-time, however, not only could this kind of dire situation be avoided, healthcare teams can be equipped with a wealth of data-enabled insights. By leveraging data to drive by-the-second decisions, they can diagnose patients much earlier and provide immediate assistance.

For best effect, real-time data should also be accompanied by historical data analysis. We need to know what happened in the past in order to provide vital clues as to what may happen in the future. In the case of patient treatment, this means having a detailed record of their medical and treatment history, as well as other records.

Many industries are now utilising smart devices which could generate vital data within a second. But in order to put all the data, past and present, to good use, what’s required is an appropriate tool or platform that can easily integrate and analyse both real-time and historical data at scale.

Clearsense is one example of a company that empowers healthcare organisations to realise measurable value from all the data that they have at their disposal. The company uses Cloudera Data Flow (CDF), a scalable, real-time streaming analytics platform that ingests, curates and analyses data for key insights and immediate actionable intelligence.

In the past, industries typically relied on data at rest or historical data collected in the past because, to put it simply, analysing real-time data was extremely difficult and complex. As such, in healthcare organisations, doctors and nurses would only base their actions and medications for a patient from his or her background, illness history and past medications.

With CDF, healthcare practitioners can now combine all the multi-format data streaming from wearable devices, Electronic Medical Records (EMRs) and hundreds of other new sources of data for further improvement of a patient’s health.

While streaming analytics for data in motion is now becoming more relevant in today’s increasingly data-driven era, one should not discount the importance of historical data that can be used to provide deeper insights and more accurate predictions.

When it comes to data in motion or data at rest, you shouldn’t choose one over the other.

Cloudera enables enterprises to leverage both. Cloudera Data Platform and Cloudera Data Flow can be used for general data analysis as well as for real-time data streaming at high volume and high scale. In addition, businesses can track data provenance and lineage of streaming data and manage and monitor edge applications and streaming sources.

To learn more about how you can do much more with your data, click here.

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