Sign up to save your podcasts
Or
Share FOSS4G NA 2024 - Geospatial Analytics with GeoParquet and Parquet - Rekha Khandhadia
Share to email
Share to Facebook
Share to X
Share to email
Share to Facebook
Share to X
Or
FOSS4G NA 2024 - Geospatial Analytics with GeoParquet and Parquet - Rekha Khandhadia
Rekha Khandhadia presents a comprehensive overview of geospatial analytics using GeoParquet and discusses challenges in traditional GIS data pipelines, while introducing the Crunchy Bridge analytics platform for enhanced data integration and efficiency.
Highlights
š Discusses traditional GIS data pipeline challenges, such as diverse formats and scaling issues.
š Introduces GeoParquet, emphasizing its open-source nature and efficient storage capabilities.
š Highlights the performance benefits of predicate pushdown in data querying.
š Explores data integration with Crunchy Bridge analytics for seamless querying of remote datasets.
š Demonstrates practical use cases, including querying geographic data and visualizing results in QGIS.
š ļø Emphasizes the importance of complex data types and efficient processing in geospatial analytics.
š„ Shares a screen recording of real-time data queries and visualizations.
For more content like this check out www.projectgeospatial.com
#GeospatialAnalytics #GeoParquet #CrunchyBridge #DataIntegration #GIS #OpenSource #DataVisualization
View all episodes
By Project Geospatial
4.2
55 ratings
Rekha Khandhadia presents a comprehensive overview of geospatial analytics using GeoParquet and discusses challenges in traditional GIS data pipelines, while introducing the Crunchy Bridge analytics platform for enhanced data integration and efficiency.
Highlights
š Discusses traditional GIS data pipeline challenges, such as diverse formats and scaling issues.
š Introduces GeoParquet, emphasizing its open-source nature and efficient storage capabilities.
š Highlights the performance benefits of predicate pushdown in data querying.
š Explores data integration with Crunchy Bridge analytics for seamless querying of remote datasets.
š Demonstrates practical use cases, including querying geographic data and visualizing results in QGIS.
š ļø Emphasizes the importance of complex data types and efficient processing in geospatial analytics.
š„ Shares a screen recording of real-time data queries and visualizations.
For more content like this check out www.projectgeospatial.com
#GeospatialAnalytics #GeoParquet #CrunchyBridge #DataIntegration #GIS #OpenSource #DataVisualization