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Cloud Native Geospatial Analytics With Apache Sedona: A HandsOn Guide For Working With LargeScale Spatial Data
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Navigating The Complexities Of LargeScale Spatial Data Can Be Daunting. In Order To Unleash The Power Of Massive And Complex Datasets, YouLl Need A CuttingEdge Tool Like Apache Sedona. This Innovative Distributed Computing System, Designed Specifically For Spatial Data, Has Diverse Applications In Fields Such As Mobility, Telematics, Agriculture, Climate Science, And More. This Book Serves As Your Guide To Leveraging This Tool, Along With Other Technologies, To Unlock The Potential Of Geospatial Analytics.Authors Pawe Tokaj, Jia Yu, And Mo Sarwat Provide Practical Solutions To The Challenges Of Working With Geospatial Data At Scale. Ideal For Developers, Data Scientists, Engineers, And Analysts, This Guide Uses RealWorld Examples To Help You Integrate Python Data Ecosystems, Apply Machine Learning, Build Geospatial Data Lakehouses, And Handle Modern Geospatial Data Formats Like Geoparquet. Understand How Apache Sedona Helps Data Practitioners Address Challenges With Geospatial Data Learn How To Run Apache Sedona, Both Locally And In Cloud Environments Efficiently Load, Query, And Analyze Geospatial Datasets Using Spatial Sql Employ Machine Learning Techniques To Derive StrategyDefining Insights From Spatial Data Manage And Optimize LargeScale Geospatial Data Within A Data Lakehouse Architecture
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