Basically the Power BI Pulse chart lets you build a line chart based on a time series where additional columns could describe certain events and their descriptions during a range of timestamps of your data set. And the beauty of this custom visualization is that it has an autoplay feature that starts playing and builds your line chart along with showing your defined event descriptions; I think it's very fascinating and it also attract people's attention to your dataset.
I used an Ottawa transit company open data set that shows bus routes, bus stop locations and bus stop times of different dates within a year to build my Power BI Pulse chart (http://data.ottawa.ca/dataset/oc-transpo-schedules). So I created a data model that contained all bus stop times within a single day. Then I added some custom events with descriptions to briefly describe various Ups & Downs for the overall time stops. So here is what I was able to create, a Pulse chart based on regular day of the OC Transpo company.
It's the same dataset that I had already used in the past for my PowerMap demo in Excel; at that time I called it as Dancing bars of OC Transpo with basically showed the same busy day with bus stop times as a fact base.
and here is a YouTube link to the complete PowerMap video: Dancing bars of OC Transpo – Busy day 3D Map of transit service for Ottawa
There is one limitation though that I had experienced building my Pulse Chart. Current version of this visualization supports only a Date hierarchy (Year-Quarter-Month-Day) based on your timestamp dataset column. However, my OC Transpo time series was only within a single day, and my expectation was to see Hours on the chart X-axis, which it didn't have.
I sent a note to Microsoft Power BI team and they were prompt enough to suggest to add this request into their pool of other Power BI ideas which then get further reviewed and used as a base for future improvement and corrections. So perhaps, in a near future, my wish will turn into reality 🙂
I hope you will find this blog post interesting and helpful. Happy data adventure!
