How TfNSW enabled self-service transport analytics

Transport for NSW, Databricks, and Data-Driven presented this online meetup on December 11, 2020. The session connected a Transport for NSW problem statement to an Operational Data Lake implementation on Azure.

It is retained as an event and customer record. Registration, the old form, and the live-session prompt have closed.

What the session covered

The published agenda moved through three views of the work:

1. The transport and reporting problem described by Transport for NSW.
2. The Azure and Databricks implementation presented by Data-Driven.
3. The self-service analytics and machine-learning use cases discussed by the group.

The original page named Databricks Delta, Databricks SQL Analytics, Spark, Azure Synapse, Azure Machine Learning, and Power Platform. Those names reflect the 2020 session, not a current architecture recommendation.

The recorded customer view

“TfNSW needed a solution to capture real-time data for every vehicle in motion across the state. This solution just gives us that so that we mine nuggets from this data at a later date. We now have an ability to self-service without waiting for someone else to curate data.”

— Sandeep Mathur, Program Manager, Transport for NSW, as listed for the 2020 event

View Sandeep Mathur’s LinkedIn profile.

The quotation and role are preserved as published. They should not be read as a current job title or as proof of every present-day platform capability.

Where to find the maintained record

The archived meetup page preserves the date, agenda, speakers, and claim boundary.

The Transport for NSW case study is the maintained source for the problem, implementation, and published result. Use it rather than inferring current architecture or data availability from this 2020 session.