CASE STUDY performing data platform , our forecasting model required two weeks and two people to manage .
To overcome our challenges , we needed a data intelligence platform and decided to centralise our data and analytics on the Databricks Data Intelligence Platform on Microsoft Azure . A year on , we ’ ve drastically modernised our forecasting model , reduced errors and costs , and gained insights for AI expansion .
How is Databricks ’ Unity Catalog helping Heathrow ensure secure and consistent data usage across the airport ?
Maximising the value of our data whilst maintaining security has always been a priority . As part of our partnership with Databricks , we decided to implement data governance with its Unity Catalog solution to secure our data and AI assets under a single permission model . By doing so , we ’ re furthering safe and consistent data use across Heathrow .
With the ability to plan predictive maintenance and optimise service interruptions with the new forecasting model , how has this impacted cost savings and traveller experience during peak travel periods ?
It ’ s important to first note that airport customer satisfaction is directly impacted by passenger wait times . In fact , if a passenger is in line for longer than five minutes , we consider it a breach of customer experience . So , by leveraging Databricks ’ solutions , we ’ ve been able to improve customer satisfaction by optimising passenger flow within varying areas . For instance , we ’ ve sped forecast insights from two weeks to four hours while decreasing the margin of error from 30 % to 10 %. Moreover , our advanced forecasting capabilities now mean we can prepare our teams for peak travel periods so they can proactively respond with efficient passenger flow , thus putting customer satisfaction at the forefront .
How has integrating Power BI with Databricks improved decision-making processes at Heathrow ?
Evolving our decision-making capabilities required cross-team collaboration . As such , we integrated Power BI to ingest data from the lakehouse into dashboards and visualisations for business reporting – thereby furthering safe and collaborative data use across Heathrow .
As you look toward establishing a centre of excellence for data and AI , how do you envision Heathrow ’ s use of MLflow and Databricks Delta Sharing evolving to support better collaboration with airlines , ground handlers and other partners ?
By implementing model tracking and data sharing , we ’ ll be able to gain a more in-depth understanding of future passenger volumes and potential service interruptions . That way , we can plan accordingly and ensure Heathrow customers always receive excellent service . We ’ ll also have the ability to further strengthen our forecasting capabilities to enhance our operations and improve airport efficiency . p
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