Reference number : GC-2017-Q4-00736, amendment number : , agreement type : G, recipient legal name : Hamilton, Howard (University of Regina), recipient country : CA, recipient province : nan, recipient city : Saskatchewan, recipient postal code : nan, program name english : Engage Plus Grants for universities, program name french : Subvention d'engagement partenarial Plus pour les universités, program purpose english : Celero Solutions requires research on predictive and visual analytics for strategic business planning.  A particular concern is making predictions about the Canadian economy and especially the business of Canadian credit unions._x000D_
      The main objectives of the research project are (1) to improve a predictive model of the Canadian credit union business that incorporates publicly available and private economic data concerning global, national, and local economic factors, and (2) to improve a dashboard that displays information about credit union health and performance in an easy to understand format. _x000D_
      Given an initial model based on auto-regressive integrated moving averages (ARIMA), a wide variety of predictive analytics techniques including vector auto-regression (VAR), machine learning (classification learning and deep learning), and data mining will be evaluated to determine whether they improve predictive accuracy. The dashboard will be improved to display the input and summarized output for a large variety of data sources. Research will be performed to determine an appropriate way for the graphical user interface (GUI) to display alerts for cases where the actual economic and business performance significantly deviates from forecasts. This information will be given for individual credit unions and also presented in the context of aggregated values._x000D_
      In the evaluation part of the research, first the improved predictive model will be implemented and verified using some artificial data. Next, we will apply the improved model to historical data to determine its effectiveness. A variety of conditions will be simulated to ensure that alerts are produced. Separately, as part of the evaluation, we will perform detailed software testing on the dashboard to ensure that all required functionality is present and works correctly and reliability. Finally, the software prototype will be evaluated in association with Celero personnel in the context of performing strategic business planning for the next year._x000D_
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_x000D_, program purpose french : Celero Solutions requires research on predictive and visual analytics for strategic business planning.  A particular concern is making predictions about the Canadian economy and especially the business of Canadian credit unions._x000D_
      The main objectives of the research project are (1) to improve a predictive model of the Canadian credit union business that incorporates publicly available and private economic data concerning global, national, and local economic factors, and (2) to improve a dashboard that displays information about credit union health and performance in an easy to understand format. _x000D_
      Given an initial model based on auto-regressive integrated moving averages (ARIMA), a wide variety of predictive analytics techniques including vector auto-regression (VAR), machine learning (classification learning and deep learning), and data mining will be evaluated to determine whether they improve predictive accuracy. The dashboard will be improved to display the input and summarized output for a large variety of data sources. Research will be performed to determine an appropriate way for the graphical user interface (GUI) to display alerts for cases where the actual economic and business performance significantly deviates from forecasts. This information will be given for individual credit unions and also presented in the context of aggregated values._x000D_
      In the evaluation part of the research, first the improved predictive model will be implemented and verified using some artificial data. Next, we will apply the improved model to historical data to determine its effectiveness. A variety of conditions will be simulated to ensure that alerts are produced. Separately, as part of the evaluation, we will perform detailed software testing on the dashboard to ensure that all required functionality is present and works correctly and reliability. Finally, the software prototype will be evaluated in association with Celero personnel in the context of performing strategic business planning for the next year._x000D_
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_x000D_, agreement title english : Predictive and visual analytics for strategic business planning, agreement title french : Predictive and visual analytics for strategic business planning, agreement number : EGP2, agreement value : 12500.0, agreement start date : 2018-01-10, agreement end date : nan, description english : nan, description french : nan, expected results english : nan, expected results french : nan, additional information english : Grant or Award spanning more than one fiscal year (2017-2018 to 2018-2019)., additional information french : Subvention ou bourse octroyée s'appliquant à plus d'un exercice financier (2017-2018 à 2018-2019)., owner organization : nserc-crsng, owner organization title : Natural Sciences and Engineering Research Council of Canada | Conseil de recherches en sciences naturelles et en génie du Canada