Designing a location intelligence platform for everyone by integrating data, analysis, and cartography
Geospatial analysis can provide deep insights into many datasets. Unfortunately the key tools to unlocking these insightsgeospatial statistics, machine learning, and meaningful cartographyremain inaccessible to nontechnical audiences. Stuart Lynn and Andy Eschbacher explore the design challenges in making these tools accessible and integrated in an intuitive location intelligence platform.
|Talk Title||Designing a location intelligence platform for everyone by integrating data, analysis, and cartography|
|Conference||Strata + Hadoop World|
|Conf Tag||Make Data Work|
|Location||New York, New York|
|Date||September 27-29, 2016|
CartoDB has enabled hundreds of thousands of users to visualize their data as beautiful maps to gain insights and share stories. However, these maps contain information that often can’t be uncovered by visualization alone. By applying geospatial statistical methods and machine learning, new stories and understanding can be extracted and predictions can be made. Applying these methods to geospatial data is powerful but also highly technical and comes with a series of caveats and complexities that are not necessarily understood by our target users. So how do you enable diverse users to access advanced methods? CartoDB’s solution has been to tightly pair analysis, data, and cartography inside an easy-to-use user interface. Stuart Lynn and Andy Eschbacher offer an overview of CartoDB’s platform, which combines an intuitive visual language to build analysis chains, novel, beautiful cartography that is tailored to communicate the results of these analyses, and an exploration interface that allows insights to be discovered in data through a simple iterative approach. Any one of these components alone is not sufficient; the interplay between them is essential to helping users understand more from geospatial data.