The defining characteristic of point cloud data is that they are large, and tools such as [Entwine](https://entwine.io) and the Entwine Point Tile specification can help you overcome their bigness. We will discuss how we used Entwine and EPT to construct point cloud web services for the [USGS 3DEP LiDAR data](https://usgs.entwine.io) of the United States as an Amazon Public Dataset. We will also demonstrate how to leverage EPT web services with open source software such as [PDAL](https://pdal.io) to extract information, enhance data utility, and reduce data volume for tasks such as filtering, object identification, and visualization. You will learn about how these tools work together with others such as [GDAL](https://www.gdal.org/) and [PROJ](https://proj4.org/) to provide data management and processing pipelines for expansive data holdings.
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