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Predictive Data Analytics

Posted by: data61

February 2, 2015

Traditional data management tools are struggling to process the flood of data generated in the digital world.

Extracting business value requires a new approach to make it easier to collect, store, analyse, visualise and dynamically act on data from separate ‘silos’ including:

  • internet browsing history and mobile application data
  • customer databases and machine logs
  • financial transactions
  • third party sources (e.g. ABS) and open data.

Data61 researchers make sense of vast amounts of unstructured data to drive business value through:

  • utilising Bayesian techniques to predict business outcomes with associated confidence levels
  • identifying changing customer behaviours early
  • detecting potential business operation failure
  • detecting anomalies, potential fraud and quantifying business risks.



As one of Australia’s largest data science research teams,  the researchers have developed a number of Big Data solutions for a growing list of high profile organisations including:

  • data workbenches for ingestion and data management
  • natural language processing modules
  • data de-identification approaches
  • privacy preserving techniques
  • recommendation engines
  • embedded analytics
  • spatio-temporal modelling
  • visualisation platforms.