Advances in GIS cloud computing paradigms have opened up possibilities for the visualization and communication of spatial data at scale. Geographic data visualising have undergone profound changes in terms of representation and interactivity (Dodge et al., 2008) whilst encapsulating the real world perception of spatial attributes and processes. The increasing availability of methods and platforms poses a great opportunity for customization of geographic visualization as well as communication across multiple medium. Spatial data visualization involves exploration, analysis, synthesis and communication (Ormeling, 2010). Therefore, reviewing and evaluating the emerging cloud based platforms in the context of the geovisualization process is very critical for the next phase of Geographic data representation where visual communication is gaining traction across multiple organizations.

Google Cloud Platforms (GCP) via its products like Google Data Studio (GDS) and Google Maps have created a unique opportunity for spatial data exploration, analysis, synthesis and presentation which are key to effective geovisualization. Through the interplay of critical product review buttressed by case studies, suitable datasets and workflows, the work explores the spatial dimension of GCP. With emphasis on visualization, general and cartographic methods were explored in the context of potential and limitation for Geoinformatics and Cartographic use.

The study explored the process of data integration, data transformation, visualization and communication using a case study approach. A conceptual framework was developed for spatial data visualization involving Geospatial Data Source, Map Design Considerations, Cartographic Methods Visualization and Evaluation. The work reviewed and adopted a customised workflow based on the design framework and include data connectors, data transformation, data validation and visualization. Various evaluation approaches such as heuristic evaluation, aspect analysis and SWOT analysis were used complementarily to ascertain the extent and overview of spatial dimensions.