Data Wrangling and Visualisation
Developing analytics-based business models require domain knowledge and technical knowledge as well, but such models are usually data driven models with limitations given by the available information. Moreover, during the ideation process of creating the business model, it is essential to manage end-user expectations.
The main aim of the module is to help the business leaders to have an effective communication with the Data Analytics/Science Team when the analytics-based business model canvas is designed. This is achieved by providing intuitive guidelines regarding the standard data wrangling and visualisation tools used in practice that are basic skills that analytics translators would need to better communicate with data engineers and data scientists.
The entire module is delivered in Tableau Desktop and modern, point-and-click data science software (e.g., Exploratory-R) by discussing analytics inclined use cases.
The main aim of this module is to introduce you to the advantages and misbeliefs of using the outputs of some standard complex data exploratory tools while creating any analytics-based business model canvas.