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Welcome to This Month In Wherobots where we highlight the latest goings on from the Wherobots & Apache Sedona community. In this edition we’re taking a look at the largest release ever in the history of Apache Sedona, the latest SedonaDB and Wherobots Cloud launch, self-service geospatial analytics, building maps with Felt, and a look at the Wherobots Online Community.
Each month we highlight special members of the community who contribute their expertise and passion to the Wherobots and Apache Sedona community. This month’s featured community members are Nara Khou Lead Data Engineer at Land O’Lakes and Cort Lunke Data & Analytics Lead at Land O’Lakes. Earlier this year Nara and Cort presented “Self-Service Geospatial Analytics Built On Databricks, Apache Sedona and R” at Databricks’ Data+AI Summit. Thanks so much Nara and Cort for sharing your success story using Apache Sedona with the community!
In this presentation Nara and Cort discuss some of the challenges of working with spatial data and how Apache Sedona can be used to address some of these difficulties in an enterprise data environment like Databricks. Cort and Nara share why they chose Apache Sedona for working with spatial data at scale to analyze watershed and cropland data. They discuss the data processing pipeline used for the project and demo the end to end data pipeline from data collection, processing and analysis using Apache Sedona, and visualization using R-Studio – all within Databricks.
Watch the recording of Nara & Cort’s Data+AI Summit Presentation
The Wherobots team was excited to reveal SedonaDB, the cloud-native spatial analytics database platform at the FOSS4G North America conference. SedonaDB builds upon the scability and stability of the Apache Sedona project bringing large-scale geospatial analytics capabilities to enterprises looking for a cloud-native solution. SedonaDB also introduces the Havasu open table format which enables efficient querying and updating of geometry and raster columns in Parquet files stored in cloud object stores such as AWS S3.
Get started with SedonaDB on Wherobots Cloud Free tier today.
The most recent release of Apache Sedona v1.5.0 was the biggest release in the history of Apache Sedona. This release includes native support for Uber H3 hexagon functions, comprehensive raster ETL and analytics support, more ST functions to enable new geospatial workloads, XYZM support, and visualization with SedonaKepler and SedonaPyDeck. This version is also available in the official Apache Sedona Docker Image. You can find more about this release in the Apache Sedona GitHub repository and read more about the v1.5.0 Apache Sedona release here.
Learn more about the latest Apache Sedona release
An important requirement for data infrastructure tools like SedonaDB and Wherobots Cloud are that they integrate well with the technology ecosystems around them. In the world of spatial databases this includes geospatial visualization tooling like the web-based mapping tool Felt. This blog post shows how to integrate the Felt API with Wherobots Cloud so we can leverage SedonaDB’s geospatial analysis capabilities using Spatial SQL then publish the results of our analysis to Felt’s beautiful web-based mapping tooling. This example uses data from BirdBuddy, which publishes data about bird sightings at its smart birdfeeders to find the range of some of our favorite bird species.
Read the blog post “Creating Collaborative Web Maps With The Felt API And Wherobots Cloud”.
The Wherobots Online Community is the forum for community members to come together, ask questions, and share their expertise and excitement about spatial analytics. This site was launched earlier this month and we’re excited to have a home for the community. Please feel free to join the community, introduce yourself, and share what you’re working on and why you’re excited about spatial analytics! We’ve also launched the Wherobots YouTube Channel as a way to share educational content about spatial analytics – please check it out and subscribe.
Join The Wherobots Online Community
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