Big data is not necessarily the best data.  The current focus on the importance of big data can often be misleading.  Large datasets can certainly provide an opportunity to derive value but having the right data is crucial for determining the best solutions and achieving desired outcomes.  Interfuze look at how understanding which relatable data sets could be used in conjunction with one another, and how these data sets can achieve powerful business insights and in this case, improve and increase safety for rail operations.

The importance of investigating your own analytics capability before investing in significant data acquisition technology.

By Branden Dekenah and Lincoln Hayes (Interfuze), and Michael Bourke (Arc Infrastructure)

Arc Infrastructure (Arc) recently worked with Interfuze to develop and implement an Australian-first data driven solution that identifies track sections at risk of experiencing a washaway event, as a result of potential flooding.

Washaway and track inundation events are a key contributor to significant derailments. To try and alleviate costs and safety risks associated with derailments, many Australian innovation workshops and studies theorised that it might be possible to predict derailments due to abnormal or intense rainfall events – referred to as washaway – by analysing past washaways and rainfall patterns.

Arc and Interfuze collected and analysed the required data to test this theory, which informed the development of a successful and first of its kind rail washaway prediction engine. Having the right data to analyse was crucial to achieving desired outcomes for this solution.

Read how data acquisition technology can affect analytics capability here.

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