Severn Class RNLI Lifeboat By Photographed by Adrian Pingstone (Own work) [Public domain], via Wikimedia CommonsSnapLogic has announced that the Royal National Lifeboat Institution (RNLI) is deploying the SnapLogic data integration platform to support and power up its analytics platform. The RNLI uses the IPaaS solution to combine data from disparate applications, including the RNLI Callout and Messaging System (RCAMS).

Founded over 200 years ago, the RNLI is a charitable organisation that saves the lives of people at risk in the seas around the United Kingdom from 238 lifeboat stations. It expects to have more than a hundred launches during the Christmas period alone. In recent years the RNLI has also helped in flood rescue efforts as climate change has brought the risks from water inland.

With the deployment of the SnapLogic IPaaS solution, the RNLI has seen several benefits.

  • The Data Engineering team has saved time. Once templates and pipelines are created, much of the repeated ETL processes are eliminated.
  • The team has also used Snap Packs, Over 600 pre-built intelligent connectors between different applications.
  • Integrations are now easier to share, scalable, standardised, and resilient.
  • SnapLogic also delivers the ability to rapidly prototype, develop, and test out ideas.

Dr Sam Prodger, head of data operations and applications at the RNLI, commented, “As a data-hungry organisation, we utilise SnapLogic as our IPaaS tool mainly because of its ease of use, which has sped up processes significantly, made the team more efficient, and increased collaboration. The most common request we get from our colleagues is to provide new data more quickly – with SnapLogic, that’s possible.”

Making the difficult, possible in the RNLI

SnapLogic has also made it possible to draw data from its mobile application, the RNLI Callout and Messaging System (RCAMS). The app provides communication that alerts volunteer crew members to a shout. Before the implementation, extracting data from the back-end platform was difficult. It can now extract data from the platform opening up the ability to measure critical response times across the country, giving it a better understanding of how quickly the teams are alerted and other metrics.

The RNLI has ambitious plans for SnapLogic. The next project is to connect data collected by the lifeboats themselves. Each lifeboat has thousands of sensors which record a huge amount of information, from water depth to information about engine performance. Using SnapLogic, it hopes to extract data from its IoT platform into its analytics platform, enabling the organisation to better protect its crews by improving the preventative maintenance of all of its lifeboats, which can cost up to £2 million. Preventative maintenance will increase the availability of lifeboats by avoiding breakdowns, helping to save lives and avoiding risks of a breakdown during a rescue.

Zahi Yaari, VP of EMEA at SnapLogic
Zahi Yaari, VP of EMEA at SnapLogic

Zahi Yaari, VP of EMEA at SnapLogic, commented, “SnapLogic believes in making a way for people to be able to work easier, whilst also making the most of data integration capabilities. We’re delighted to be working with the RNLI to ensure they can do their vital work without distraction. This is why intelligent, easy-to-use and AI-driven integration and automation makes all the difference.”

Enterprise Times: What does this mean

For SnapLogic, having such a well-known and respected brand applying its IPaaS solution is huge. However, what is missing from the release are the data integrations that it has already enabled. The RNLI has a sophisticated GIS analytics platform powered by ArcGIS Server and ArcGIS Online. It also makes the data available to third parties through the ArcGIS Online platform. This is partly powered by its Lifesaving Activity Reporting (LSAR) Data Warehouse, which presumably the SnapLogic platform administrates the data flows to.

While some of the benefits of the new solution are listed by SnapLogic, the second-order benefits will come from the changes the RNLI will make as a result of having the data accessible. While these may be powered by the analytics platform it uses, they wouldn’t have been possible without the integration in the first place. A case study, further down the road, could be interesting, but it would be wise to have it look at the whole data architecture of the RNLI and what it has achieved with its modern technology stack.


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