Isbn: 9781098173999 - cloud native geospatial analytics with apache sedona: a hands-on guide for working with large-scale spatial data (34 resultados)

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Paperback or Softback. Condición: New. Cloud Native Geospatial Analytics with Apache Sedona: A Hands-On Guide for Working with Large-Scale Spatial Data. Book.

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Paperback. Condición: New. Navigating the complexities of large-scale spatial data can be daunting. In order to unleash the power of massive and complex datasets, you'll need a cutting-edge 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 Pawel 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 real-world examples to help you integrate Python data ecosystems, apply machine learning, construct geospatial data lakehouses, and handle modern geospatial data formats like GeoParquet.Understand how Apache Sedona helps data practitioners address challenges with geospatial dataLearn how to run Apache Sedona, both locally and in cloud environmentsEfficiently load, query, and analyze geospatial datasets using spatial SQLEmploy machine learning techniques to derive strategy-defining insights from spatial dataManage and optimize large-scale geospatial data within a data lakehouse architecture. …

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Paperback. Condición: new. Paperback. Navigating the complexities of large-scale spatial data can be daunting. In order to unleash the power of massive and complex datasets, you'll need a cutting-edge 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 Pawel 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 real-world examples to help you integrate Python data ecosystems, apply machine learning, construct geospatial data lakehouses, and handle modern geospatial data formats like GeoParquet.Understand how Apache Sedona helps data practitioners address challenges with geospatial dataLearn how to run Apache Sedona, both locally and in cloud environmentsEfficiently load, query, and analyze geospatial datasets using spatial SQLEmploy machine learning techniques to derive strategy-defining insights from spatial dataManage and optimize large-scale geospatial data within a data lakehouse architecture 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. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.…

Paperback. Condición: New. Navigating the complexities of large-scale spatial data can be daunting. In order to unleash the power of massive and complex datasets, you'll need a cutting-edge 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 Pawel 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 real-world examples to help you integrate Python data ecosystems, apply machine learning, construct geospatial data lakehouses, and handle modern geospatial data formats like GeoParquet.Understand how Apache Sedona helps data practitioners address challenges with geospatial dataLearn how to run Apache Sedona, both locally and in cloud environmentsEfficiently load, query, and analyze geospatial datasets using spatial SQLEmploy machine learning techniques to derive strategy-defining insights from spatial dataManage and optimize large-scale geospatial data within a data lakehouse architecture. …

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Taschenbuch. Condición: Neu. Neuware -Navigating the complexities of large-scale spatial data can be daunting. In order to unleash the power of massive and complex datasets, you'll need a cutting-edge 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 Paweł 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 real-world 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 strategy-defining insights from spatial data - Manage and optimize large-scale geospatial data within a data lakehouse architecture 300 pp. Englisch.…

Taschenbuch. Condición: Neu. Neuware -Navigating the complexities of large-scale spatial data can be daunting. In order to unleash the power of massive and complex datasets, you'll need a cutting-edge 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 Paweł 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 real-world 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 strategy-defining insights from spatial data - Manage and optimize large-scale geospatial data within a data lakehouse architecture 300 pp. Englisch.…

Taschenbuch. Condición: Neu. Neuware -Navigating the complexities of large-scale spatial data can be daunting. In order to unleash the power of massive and complex datasets, you'll need a cutting-edge 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 Paweł 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 real-world 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 strategy-defining insights from spatial data - Manage and optimize large-scale geospatial data within a data lakehouse architecture.…

Paperback. Condición: New. Navigating the complexities of large-scale spatial data can be daunting. In order to unleash the power of massive and complex datasets, you'll need a cutting-edge 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 Pawel 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 real-world examples to help you integrate Python data ecosystems, apply machine learning, construct geospatial data lakehouses, and handle modern geospatial data formats like GeoParquet.Understand how Apache Sedona helps data practitioners address challenges with geospatial dataLearn how to run Apache Sedona, both locally and in cloud environmentsEfficiently load, query, and analyze geospatial datasets using spatial SQLEmploy machine learning techniques to derive strategy-defining insights from spatial dataManage and optimize large-scale geospatial data within a data lakehouse architecture. …

Condición: New.

Taschenbuch. Condición: Neu. Neuware - Navigating the complexities of large-scale spatial data can be daunting. In order to unleash the power of massive and complex datasets, you'll need a cutting-edge 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 Paweł 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 real-world 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 strategy-defining insights from spatial data - Manage and optimize large-scale geospatial data within a data lakehouse architecture.…

Paperback. Condición: new. Paperback. Navigating the complexities of large-scale spatial data can be daunting. In order to unleash the power of massive and complex datasets, you'll need a cutting-edge 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 Pawel 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 real-world examples to help you integrate Python data ecosystems, apply machine learning, construct geospatial data lakehouses, and handle modern geospatial data formats like GeoParquet.Understand how Apache Sedona helps data practitioners address challenges with geospatial dataLearn how to run Apache Sedona, both locally and in cloud environmentsEfficiently load, query, and analyze geospatial datasets using spatial SQLEmploy machine learning techniques to derive strategy-defining insights from spatial dataManage and optimize large-scale geospatial data within a data lakehouse architecture 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. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability.…

Taschenbuch. Condición: Neu. Cloud Native Geospatial Analytics with Apache Sedona | A Hands-On Guide For Working With Large-Scale Spatial Data | Pawel Tokaj (u. a.) | Taschenbuch | Einband - flex.(Paperback) | Englisch | 2025 | O'Reilly Media | EAN 9781098173999 | Verantwortliche Person für die EU: Libri GmbH, Europaallee 1, 36244 Bad Hersfeld, gpsr[at]libri[dot]de | Anbieter: preigu. …

Taschenbuch. Condición: Neu. Neuware -Navigating the complexities of large-scale spatial data can be daunting. In order to unleash the power of massive and complex datasets, you'll need a cutting-edge 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 Paweł 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 real-world 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 strategy-defining insights from spatial data - Manage and optimize large-scale geospatial data within a data lakehouse architectureLibri GmbH, Europaallee 1, 36244 Bad Hersfeld 300 pp. Englisch.…