Yuri Zhylyuk > Data Visualisation Samples    View my profile on LinkedIn

Dashboard: AU International Trade | Merchandise Exports
Live App: https://mb.dataninjas.com.au/public/dashboard/4cc109f0-f128-4619-b06f-20492b00e639

This dashboard renders Australian Bureau of Statistic Merchandise Exports data in Metabase. Apply filters at the top of the page to explore data by various dimensions.

Metabase (https://metabase.com) is very easy and cost efficient to set up and run. The tool itself is free and open source. My demo server is currently running in a Docker container on AWS.

Metabase is a great (and pragmatic) choice when you are on a tight budget and have a very limited time frame to get a BI/Reporting solution set up and available to your end users. Thanks to its modest TCO and practical simplicity it can also serve well as an interim BI solution, so the end users can start working with your data asap, while still deciding on the bigger picture of the BI ecosystem and evaluating other tools.

Cloud Computing, Automation, Data Visualization, Dashboards, ABS, Economy, Metabase, Python, Year 2020
Visualisation of selected statistical tables from the Reserve Bank of Australia website
Live App: http://dataviz.yznotes.com/au-economy-stats

This is part of a solution for abstracting/streamlining automated rendering of data visualisations as standalone single-page html reports (in this particular case using Plotly Python library).

The idea behind this solution is to simplify and significantly reduce time spent on designing basic reports; and when required - have such reports generated automatically as part of a serverless data pipeline or on some trigger (e.g. using AWS S3, Lambda and Step Functions, etc.).

Most of the underlying datasets are updated only monthly or quarterly (and unfortunately with some delays). One dataset that is updated more frequently is 'RBA Balance Sheet Weekly Summary'. It is also an interesting one to watch from a Quantitative Easing perspective.

Cloud Computing, Automation, Data Visualization, Dashboards, RBA, Economy, Plotly, Python, Year 2020
Dashboard: COVID 19, v2 (tracking)
Live App: http://dataviz.yznotes.com/covid19/v2

Dashboard for tracking COVID 19 progression by countries over time, refreshed daily at 0:00 UTC. It uses the same data as dashboard below (version 1) but is desined with a focus on tracking daily rate changes globally and by country.

[By Country] section provides information for top 20 (by number of currently infected) countries by default. You can use [Select Countries] menu for creating your own country list, which can be handy for comparison and daily monitoring. All timeline charts start from Jan 22 for convenient comparison between countries. [Last 24h] numbers are indicative, based on cumulative counts from the previous day.

Cloud Computing, Automation, Web Scrapping, Data Visualization, Public Health, Year 2020
Dashboard: COVID 19, v1 (exploration)
Live App: http://dataviz.yznotes.com/covid19

Dashboard that allows exploring COVID 19 progression by regions and countries over time, refreshed daily at 0:00 UTC.

Data is rendered as a multidimensional visualisation. Use filters at the top of the dashboard to select specific Region or Country. Dashboard URL can be shared with the dashboard filters pre-filled.

Cloud Computing, Automation, Web Scrapping, Data Visualization, Public Health, Year 2020
Share Market Short / Long Signals
Live App: [Not Available - Confidential Data]

Application that collects and analyses information related to Australian Share Market and produces daily Long or Short recommendations for about 2,000 individual tickers.

The App runs on AWS infrastructure using AWS Lambda, Batch, Step Functions, S3 and Athena.

Cloud Computing, Technical Analysis, Machine Learning, Automation, Web Scrapping, Data Visualization, Year 2019/2020
Dashboard: Crime by Suburb and Offence Type
Live App: http://dataviz.yznotes.com/crime-vic-2016

This App visualises Number of offences by suburbs in VIC, Australia and offence type, year ending December 2016.

The data is rendered as a multidimensional visualisation. All charts, including Crime Map are inter-connected and interactive, so you should be able to narrow down data to a subset of your interest within just a few mouse clicks. You can switch between Actual Offence Numbers and Crime Rate data views / measurements in the navigation bar.

Data Visualization, Exploratory Data Analysis, Dashboard, Year 2017
Real Time Sales Analytics
Live App: [Not Available - Confidential Data]

Web Application that asynchronously collects, aggregates and visualises data from about 70 stores across Australia and New Zealand. All calculations and charts are updated with every new transaction.

On the photo the application is running on 55'' TV screen with Raspberry Pi as a client.

Data Visualization, Dashboard, Real Time Analytics, Year 2015/2016
Experimenting with Twitter API, Text Mining, Word Cloud and d3.js Visualisation Library
Live App: http://words.yznotes.com

This Application collects Tweets posted in Melbourne, VIC (based on geotagging), does some Natural Language Processing and renders a Word Cloud of the most popular words and a 'Tweet Rate' Chart for the last 24 hours.

Data and visualisations are refreshed every 10 minutes 24/7.
Runs on Amazon Web Services.

Twitter, Natural Language Processing, Cloud Computing, Word Cloud, Data Visualization, Automation, Year 2015
VTAC Tertiary Offers 2014 Heat Map (by biggest VIC unies)
Live App: http://dataviz.yznotes.com/viz_map_vtac2014

As name suggests, this Heat Map represents density of students that have been offered a place at several biggest Universities in Victoria.

Contributors: Nghiem Tran

Google Maps API, Heat Map, VTAC, Year 2014
Dynamic Pivoting and Visualisation
Live App: [Not Available - Confidential Data]

Custom solution for automated data collection, cleansing and reporting (including customised point-click dynamic pivoting).

This was implemented as a web application that collects raw data from pre-defined web sources, then applies some cleansing and aggregation and feeds results into dashboards and visualisations.

Automation, Cloud Computing, Python Data Analysis Tools, Visualization, Dashboard, Data Pivoting, ETL, Data Cleansing, Year 2014