Dr John Gwinyai (Gwin) NYAKUENGAMA is the founder of DatAnalytics, an Australian small business which provides ethical and reliable advanced data analytics and advice. Gwin is a seasoned data scientist and knowledge broker with over 20 years of combined work experience in the public and private sectors. He has a strong and ethical stakeholder engagement and developed business acumen. Gwin has worked on nationally-significant, Australian Government socio-economic programmes in OHS, Education and Employment portfolios. He also worked on several joint-discovery projects between the Australian National University (ANU), the University of Melbourne, CSIRO and Australian and New Zealand Forestry industries in Pinus radiata genetics and silviculture.
Gwin holds a Doctorate in Quantitative Genetics from the University of Melbourne, a B.Sc. Forestry (with First Class Honours) from the ANU and a graduate diploma in Public Sector Leadership (with distinction) from Griffith University. He also holds a diploma in French (with distinction) from Cavilum de Vichy, France.
Gwin is a member of the Statistical Society of Australia, the Stata Journal and several user-groups. He participates in conferences and machine learning webinars of Gartner Magic Quadrant for Data Science and Machine Learning Platforms.
Gwin worked on several collaborative projects between government, the CSIRO-Forestry and Forest Products, the ANU and the University of Melbourne. He discovered the genetic basis of inheritance of industry-significant wood and fibre traits in Pinus Radiata D. Don; the wood microstructural reason for the thermomechanical superiority of NZ55, a radiata pine family; and the differential impact of late-age application of K-P-N fertilizers on the anatomical and physical properties of Pinus Radiata D. Don.
Gwin successfully undertook research and reporting thorough the analysis of many complex and very large, national administrative and survey datasets, including: National Coroners Information System, National Hospital and Morbidity Data, National Mesothelioma Register, Non-Government Schools Financial Questionnaire, the ABS 2011 Census, The Household, Income and Labour Dynamics in Australia (HILDA) Survey, Research Evaluation Dataset and Longitudinal Study of Indigenous Children, MYSCHOOL 2010 data, Centrelink Income Support data and the VET Student Data Collection.
Gwin successfully undertook quantitative data analysis and research to provide the evidence that underpinned several major Australian social reforms: Quantitatively evaluated the impact the Welfare to Work policy on people on income support, a Howard Government signature employment policy. Effectively provided a data support service (high-end data modelling, microsimulation and analytics) to support Commonwealth position papers for the Gonski Reforms and other socio-economic reforms. He successfully setup the phased-implementation of the Nationally Consistent Data on Students with Disability in 2013-2015. He led a national data collection project on implementation of the COAG 2013 decision to improve student attendance rates and achieve a 90 per cent attendance benchmark. Gwin provided rigorous data analytics support that underpinned the 2016-17 VET FEE-HELP Reforms.
Gwin has authored two academic theses, seven peer-reviewed scientific journal papers, countless confidential industry and government reports, and several national and international conference papers. He peer-reviewed scientific journal papers at CSIRO and commissioned consultants' reports to the Australian Federal Government. He successfully led a small team that drafted and designed the Schools and Youth Data Strategy and Data Compendium. He provided secretariat services to Federal Government Research Reference Groups in Schools and at the National Occupational Health and Safety Commission.
Gwin designs coherent organisational data strategies covering data governance, data collection, data preparation, exploratory data analysis, advanced statistical data analyses (including Structural Equation Modelling, time-series, survey-, survival-, panel-data analysis), data visualization, mapping and reporting.
Using his extensive applied experience with state-of-the-art software, Gwin tailors a data analysis and reporting regime to business objectives, pressure points (e.g. time and IT environment) and the nature of individual datasets (e.g. data type, completeness and internal structure).
Gwin's preferred tools-of-the-trade for data preparation, advanced data analytics, text and sentiment analysis, supervised and unsupervised machine learning and microsimulation are SAS, SQL, Stata, QDA Miner / WordStat, h2o‑AutoML, R, RapidMiner and ADMOD and STINMOD. Gwin employs the following tools for data visualization and mapping: Stata, R, Tibco Spotfire, Tableau, Microsoft PowerBI and MapInfo.
Gwin is a passionate promoter and long-term user of Stata for advanced data analytics of large administrative and survey data.
Over several years, Gwin championed organisational capacity building by training staff to use Stata and by managing the procurement and dissemination of Stata licenses and the Stata Journal.
In April 2018, Gwin co-delivered a four-day Stata training course with Survey Design and Analysis Services to a major ACT government department covering Introduction, Advanced Data Analysis, Advanced Graphics and Survey Data Analysis. At the 2017 Oceania Stata Users Group Meeting, he talked about "Stata: A key strategic statistical tool of choice in major impact evaluations of socioeconomic programs".
He recently blogged on his website https://dat-analytics.net/ about logistic regression in Stata and RapidMiner and on survival data analysis in Stata.
He is the Scientific Committee Chair of the 2019 – Oceania Stata Conference.