Data Visualization Predictions 2025
Discover emerging AI-driven trends transforming data visualization by 2025.
Tips for Creating Better-Looking PowerBI Dashboards
Create better PowerBI designs and solutions to help you communicate and connect with your audience.
Bad vs Good Data Viz: A Simple Bar Chart Example
Exploring the fine line between clarity and clutter in data visualization for more effective data storytelling.
Reimagining Data Science: The Rise of LLM-Powered Agents
Generative AI transforming data science, analytics, and visualization with LLM-powered agents.
Data-Driven Solutions to Help You Elevate Your Marketing Efforts Today
Elevating marketing with data science: segmentation, recommenders, RFM analysis.
Mastering Data Visualisation and Storytelling: A Guide for Leaders
Enhancing data teams and leaders with design, communication and storytelling techniques.
Elevate Your Data Visualisation and Storytelling Skills
Turn complex ideas and data into stories that resonate with your audience.
A D3.js Bar Chart Race of COVID-19 cases
This is a bar chart race animation of daily COVID19 cases created using D3.js and Observable.
Geocoding Data in Google Sheets
This post shows how easy it can be to geocode data using a custom script with google apps script in Google Sheets.
Creating Fake (Mock) Data with Python
Mocking up data for analytics, datawarehouse or unit test can be challenging. This Python package is a fast and easy way to generate fake (mock) data.
Video Interview: Powering Customer Success with Data Science & Analytics
An interview with Mike Sager, Vice-President of Customer Success of SiteMinder.
Accelerated Computing for Innovation Conference 2018
Highlights from the ACIC18 presented by The Sydney Informatics Hub at the University of Sydney
How to Get Started In Data Science & Analytics
Slides for a talk I gave at Academy Xi on how to get into data science and analytics.
The 4 Core Competencies of the Future-Proof Data Scientist
What are the key capabilities of a successful data science and analytics professional - now and in the future’? What are the things I should learn if I want to become a really good data science and analytics professional?
3 Things I Learned Helping Australia’s Leading Creative Agency Win A Large Analytics Project In Less Than A Week
Three key learnings from a recent analytics project in partnership with The Works, a leading creative agency.
Data Science and Analytics Panel @ Academy Xi: The Age of Big Data
Joining me at Academy Xi are experts from leading organisations who will share their perspectives on all things big data and analytics.
DASAMA™ - Data Science and Analytics Maturity Assessment model
The DASAMA™ model has been developed to help organisations gain visibility on their data science and analytics journey.
sizeR - Helping you decide which size to buy
In this blog post I wanted to build a simple solution to help online shoppers decide on the best size of clothes they should buy while online.
4 Elements That Can Make or Break Your Data Analytics Initiative
While all of these elements are non-data related, I'd argue they can have as much of an impact on your data analytics initiative as issues relating to data quality, choice of analytical tool, time spent fine-tuning algorithms, etc.
Literacy and Numeracy Among Young Australians: NAPLAN 2017 Preliminary Results Dashboard
This is a mobile-friendly interactive dashboard created in Tableau looking at some data from NAPLAN 2017 Preliminary results.
Time Series Forecasting in R with Google Analytics Data
Data that are obtained in series of points over an equally spaced period of time are generally referred to as Time series data.
Temporary Skilled Migration in Australia - A Overview on 457 Visa Holders
This is a mobile-friendly interactive dashboard looking at data for holders of visa subclass 457 over the past 6 years (2010-2016) in Australia.
Calculating Compound Annual Growth Rates (CAGR) in Python
CAGR measures the mean growth rates of money or units / quantities of something over the years. This is a simple function in Python to calculate CAGR.
Introduction to Principal Component Analysis (PCA) in Unsupervised Learning Settings
Principal Component Analysis (PCA) is a popular method used in statistical learning approaches.
Visualisation & Storytelling - Best Practices and Examples in the Context of Data Analytics
This is a bunch of slides I put together for a talk I gave recently on data visualisation and storytelling in the context of analytics.
Quick Guide: Interpreting Simple Linear Model Output in R
Linear regression models are a key part of the family of supervised learning models.
Using R for a Simple K-Means Clustering Exercise
K-Means is a clustering approach that belogs to the class of unsupervised statistical learning methods.
Visualising Growth in Salary vs Donation in Australia over the past 20 years
This is a visualisation created using Plotly.
Intro to Classification Problems: Simple Logistic Regression for Churn Modelling
When we study approaches for predicting qualitative responses, we study classification problems.
Simple Excel Data Wrangling with R
Today we are going to deal with some Microsoft Excel spreadsheet data in R.
Employee Average Weekly Earnings Estimates in Australia - A Tableau Public Viz
This visualisation is a product of the data wrangling work done in a previous post.
Kaggle Otto Group Challenge - An initial Random Forest approach
Thoughts and a simple approach to a Kaggle competition using Random Forest in Parallel
Resampling with the Validation Set Approach - An Example in R
Resampling is a technique that allows us to repeatedly draw samples from a set of observations and to refit a model on each sample in order to obtain additional information.
Multiple Regression Analysis in R - First Steps
In this example we'll extend the concept of linear regression to include multiple predictors.
Simple Linear Regression - An example using R
Linear regression is a type of supervised statistical learning approach that is useful for predicting a quantitative response Y.