{"product_id":"cloud-native-geospatial-analytics-with-apache-sedona-a-hands-on-guide-for-working-with-large-scale-spatial-data-9781098173999","title":"Cloud Native Geospatial Analytics with Apache Sedona: A Hands-On Guide for Working with Large-Scale Spatial Data","description":"\u003cp\u003eNavigating 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.\u003c\/p\u003e \u003cp\u003eAuthors Pawe\u0026amp;lstrok; 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.\u003c\/p\u003e \u003cul\u003e\n\u003cli\u003eUnderstand how Apache Sedona helps data practitioners address challenges with geospatial data\u003c\/li\u003e \u003cli\u003eLearn how to run Apache Sedona, both locally and in cloud environments\u003c\/li\u003e \u003cli\u003eEfficiently load, query, and analyze geospatial datasets using spatial SQL\u003c\/li\u003e \u003cli\u003eEmploy machine learning techniques to derive strategy-defining insights from spatial data\u003c\/li\u003e \u003cli\u003eManage and optimize large-scale geospatial data within a data lakehouse architecture\u003c\/li\u003e\n\u003c\/ul\u003e\u003cbr\u003e\u003cbr\u003e\u003cbr\u003e\u003cb\u003eAbout the Author\u003c\/b\u003e\u003cbr\u003e\u003cb\u003e\u003ci\u003eTokaj, Pawel:\u003c\/i\u003e\u003c\/b\u003e - \u003cp\u003ePawel Tokaj is a staff software engineer at Splunk and a PMC member of the Apache Sedona project who enjoys writing reliable, efficient software that helps others. His love for geospatial data started at the Warsaw University of Technology, where he graduated in geodesy and cartography. \u003c\/p\u003e \u003cp\u003ePawel's primary focus areas are distributed databases and systems, cloud computing, and geospatial data processing. He believes that open source projects make knowledge more accessible; he has contributed to Apache Sedona, Open Lineage, and Airbyte. He attends various conferences or meetups where he shares his knowledge as a speaker or participant. He is a technology nerd, spending a lot of his spare time reading books and articles and developing open source software.\u003c\/p\u003e\u003cb\u003e\u003ci\u003eYu, Jia:\u003c\/i\u003e\u003c\/b\u003e - \u003cp\u003eJia Yu is a cofounder of Wherobots, a venture-backed company for helping businesses to drive insights from spatiotemporal data. He was a tenure-track assistant professor of computer science at Washington State University from 2020 to 2023. He obtained his Ph.D. in computer science from Arizona State University. \u003c\/p\u003e \u003cp\u003e Jia's research focuses on large-scale database systems and geospatial data management. In particular, he worked on distributed geospatial data management systems, database indexing, and geospatial data visualization. Jia's research outcomes have appeared in the most prestigious database\/GIS conferences and journals, including SIGMOD, VLDB, ICDE, SIGSPATIAL and \u003cem\u003eVLDB Journal\u003c\/em\u003e. He is also the main contributor on several open sourced research projects, such as Apache Sedona, a cluster computing framework for processing big spatial data, which receives one million downloads per month and has users\/contributors from major companies.\u003cb\u003e\u003ci\u003eSarwat, Mo:\u003c\/i\u003e\u003c\/b\u003e - \u003c\/p\u003e\u003cp\u003eMo Sarwat is the CEO of Wherobots and cocreator of Apache Sedona. At Wherobots he is spearheading a team developing a cloud data platform equipped with a brain and memory for our planet to solve the world's most pressing issues. Wherobots is founded by the creators of Apache Sedona, an open source framework designed for large-scale spatial data processing in cloud and on-prem deployments. \u003c\/p\u003e \u003cp\u003eMo taught and conducted research at Arizona State University in the fields of large-scale data processing, databases, data analytics, and AI data infrastructure. With over a decade of experience in academia and industry, Mo has published more than 60 peer-reviewed papers, received two best research paper awards, and been named an Early Career Distinguished Lecturer by the IEEE Mobile Data Management community. Mo is also a recipient of the 2019 National Science Foundation CAREER award, one of the most prestigious honors for young faculty members.\u003c\/p\u003e \u003cp\u003eHis mission is to advance the state of the art in data management and AI to empower data-driven decision making for a wide range of applications, such as transportation, mobility, and environmental monitoring. He is passionate about developing robust and scalable data systems that can handle complex and massive datasets and leverage AI and machine learning techniques to extract valuable insights and patterns.\u003c\/p\u003e","brand":"O'Reilly Media","offers":[{"title":"Default Title","offer_id":52033969094930,"sku":"9781098173999","price":69.99,"currency_code":"USD","in_stock":false}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0831\/4771\/8930\/files\/img_d90b8fae-2bf0-459a-9ace-df2c843187f6.jpg?v=1770982601","url":"https:\/\/surprise-castle.myshopify.com\/products\/cloud-native-geospatial-analytics-with-apache-sedona-a-hands-on-guide-for-working-with-large-scale-spatial-data-9781098173999","provider":"Surprise Castle","version":"1.0","type":"link"}