Inspiration
We were excited to tackle the unique challenges that come with the analysis, representation and visualization of time series analysis.
What it does
Heartbeat simulates a real-time data stream that is analyzed and refreshed every second (or quicker!). It allows the end-user to get a top-down perspective on how their order book and get a pulse on their market performance. Additionally, Heartbeat also tracks the logical flow of every transaction it analyzes, flagging those transactions it has identified as anomalies and/or errors, giving the end-user the ability to analyze these incidents further.
How we built it
We built this dashboard and stream simulation using Python3 with Plotly and Streamlit.
Challenges we ran into
The biggest challenge we ran into was effectively simulating the time series data to match real-time, given that there were hundreds of transactions, requests and cancellations within each second.
Accomplishments that we're proud of
We managed to learn and implement new libraries (and languages) in such a short amount of time.
What we learned
We learnt how to effectively work with people we had just met, and learnt various new techniques on how to visualize data.
What's next for Heartbeat
Someday, Heartbeat too, will be unplugged. Please show it as much love as we have before that day comes.
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