Case Study: Aginic achieves eye-catching real-time bike-sharing dashboards with Elastic Canvas

Eye-catching Canvas dashboards on top of bike sharing data

Aginic, an Australian data analytics consultancy and Elastic partner, showcased new Canvas and SQL features at an Elastic Brisbane meetup by tackling a bike‑sharing use case. The challenge was to combine historical trip data and near‑real‑time station status feeds into eye‑catching, actionable visualizations that could support rental rate improvements, inventory monitoring and better commuter experience.

The team ingested CitiBike trip data via Logstash from S3 and polled live station JSON with a custom Python fetch–sleep loop into Elasticsearch, then built a branded Kibana Canvas workpad to present transactional and point‑in‑time metrics. The demo surfaced real‑time KPIs (currently renting, total bikes, eBikes, docks per station, disabled bikes, station table), demonstrated low‑cost animated infographics and faster iteration, and can be extended into maintainer dashboards or public screens to boost usability and engagement.

Aginic

Ruben Slabbert

Cloud Data Engineer and Application Developer