This hands-on tutorial explains how a Business Analyst without deep statistical know-how can create a time-series forecast.
Using real data from a bicycle rental scheme in London you will forecast the demand for these bikes. With the help of additional predictor variables, such as information about the temperature or rain, the forecast is further improved.
Please note that this guide is giving a high-level introductory overview and only shows a small fraction of the available functionality.
Download from GitHub
- Data (see the above Tutorial for information on the source of the data and the rights on the data)
Update July 2016: With the release of SAP Predictive Analytics 3.0, it is possible to easily automate the forecasting of many time-series using a graphical user interface. Please see this article for details: