SQLBits 2024
Flight of Insights: Navigating Data Turbulence with SQL Modelling and Visualisation
When navigating a project, how can we identify and avoid potential bird strikes? How can we make assumptions about a project that has not yet even taken off? In this session we will tie back to the story of Captain Sully, demonstrating that having the correct data model and taking into account all data and risks, enables you to build the correct visualisation.
Everyone remembers the Miracle on the Hudson. A day when quick instincts and decision making undoubtedly saved many lives. Or did it? As the story portrays, many aviation authorities doubted the actions that were taken were correct. But, in fact, their assumptions of the situation were flawed and it wasn't until reality was added did the story make sense. With the complexity of modern data analytics projects, the same can be true.
So how can we identify and avoid potential bird strikes? How can we make assumptions about a project that has not yet even taken off? In this session we will tie back to the story of Sully, explaining that having the correct data model and taking into account all data and risks enables you to build the correct visualisation.
Including examples of how to overcome project challengers who may not understand the technical data landscape.
Focusing on the fact that data is king and visualisation is queen and without the right data modelling and structure your data visualisations can't give you accurate insights.
So how can we identify and avoid potential bird strikes? How can we make assumptions about a project that has not yet even taken off? In this session we will tie back to the story of Sully, explaining that having the correct data model and taking into account all data and risks enables you to build the correct visualisation.
Including examples of how to overcome project challengers who may not understand the technical data landscape.
Focusing on the fact that data is king and visualisation is queen and without the right data modelling and structure your data visualisations can't give you accurate insights.