who is orbisant analytics?
Orbisant Analytics is an open data science and analytics network and platform focused on the scientific generation of findings from publicly-available data. Orbisant leverages the expertise of its contributors across a range of analytical techniques including data science, machine learning, statistical modelling, mathematical modelling, and data visualisation.
what does orbisant mean?
Orbisant gets its name from the portmanteau of “orb” and “cognisant.” The “cognisant” portion is simple, reflecting the broader societal demand to be more aware of trends and analytical insights. The “orb” portion is more operational, as it describes our three key focus areas (or orbs) as a platform:
1. Rigorous quantitative investigation of publicly-available data
2. Factual exposition of findings
3. Engaging data visualisation
The first, and most important point, "rigorous quantitative investigation of publicly-available data" is what makes us unique. We are not a market research firm, we are not a journalistic news feed nor an academic journal. Instead, we occupy the middle ground of scientific literature and commercially-relevant information dissemination with our work exploring data that any member of the public can freely access and applying scientific rigour to its exploration. The end goal of each piece of analysis we do is not necessarily to shift a policy needle or generate strategic information, but rather to start a conversation that can lead to those outcomes, if the topic requires it. Because of Orbisant's agnosticism toward the topic of exploration, it may be the case that some of our work is focused on the generation of findings for the sake of pursuing knowledge or just general interest. This means readers of our work get access to a broad range of topics that are not limited to the traditional demand boundaries.
Our team
trent henderson
Trent is the founder of Orbisant Analytics and is a Senior Data Scientist for the consulting firm Nous Group and a computational statistics PhD student at The University of Sydney. Trent is a published peer-reviewed author and statistical software developer and has led many complex data science and research projects for private and public sector clients and academia across the last 6 years. Trent is particularly motivated by Bayesian statistics, time-series modelling, causal inference, and data visualisation. Trent’s GitHub is available here. Any views expressed here are Trent’s and not that of Nous Group.