Location analytics by Marc Planaguma at Big Data Spain 2014
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http://www.bigdataspain.org/2014/conference/location-analytics While the implementation of analytic operations on distributed computing frameworks has been widely describing, enabling the computational core of a Big Data system with capabilities for supporting geospatial querying on data is yet a challenging issue. This session aims to target that specific aspect by reviewing how researchers at BDigital Technology Centre have designed and implemented a stack for advanced Machine Learning on Urban Data by providing a way to geoquery massive amounts of HDFS data from Spark processes without hindering the overall system performance.
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Location analytics by Marc Planaguma at Big Data Spain 2014
- 1. SPATIAL DATA ANALYTICS MARC PLANAGUMÀ LEAD DATA ENGINEER AND RESEARCHER BDIGITAL
- 2. Ciudad 2020 Exploratory lines and further work Joana Simoes, BDigital 27/05/2014 Scaling up a in a world of geolocated data Marc Planagumà, BDigital Technology Centre
- 3. Our team
- 4. Our work
- 5. A world of geolocated data
- 6. Applications
- 9. Spatial data analytics Spatial analysis or spatial statistics includes any of the formal techniques which studies entities using their topological, geometric or geographic properties
- 10. Spatial data analytics Basic Spatial Types Line Point Polygon * plus others
- 11. Spatial data analytics Geometries
- 12. Spatial data analytics Operations Contains Within
- 13. Spatial data analytics Operations Equals Disjoint
- 14. Spatial data analytics Operations Touches Overlaps Crosses
- 15. Spatial data analytics Operations Distance
- 16. Spatial data analytics Operations Union Difference
- 17. Spatial data analytics Operations Intersection Symmetric Diff
- 18. Spatial data analytics Complex operations Buffering Convex Hull
- 19. Spatial data analytics Complex operations Area
- 20. Spatial data analytics Geospatial data mining techniques Density-based clustering Hierarchy-based clustering
- 21. Spatial data analytics Geospatial data mining techniques Heatmaps
- 22. Spatial data analytics Geospatial data mining techniques Trajectory mining
- 23. Spatial data analytics Geospatial data mining techniques Geospatial querying Spatial anomalies Geographically weighted regressions Self-organizing Maps Agent-based modeling
- 24. Our Use Cases Customer activity tracking Spatial data analytics Where does people buy? What is the profile of the buyer? Traffic agencies Can we predict the traffic status? Can we predict the traffic incidences?
- 25. Spatial data analytics Our Datasets Twitter (Point) Meteo (Polygon) Traffic status (Multi-Line-String) Traffic incidence (Multi-Point) Credit card ops (Multi-Point) Demographic (Point & Polygon) Shapefiles (Multi-Polygon)
- 26. Our Tools Spatial data analytics Queries Clustering Heat maps Trajectory Anomaly detection
- 27. Our Stacks
- 28. Spatial data analytics Old School Stack - Why Not? PostGIS Hadoop + GIS Kibana Tools ElasticSearch
- 30. Spatial data analytics Hadoop Stack - The new Classic PostGIS Hadoop + GIS Kibana Tools ElasticSearch
- 32. Spatial data analytics Complete Stack - Big Data GIS PostGIS Hadoop + GIS Kibana Tools ElasticSearch
- 34. Do’s and Don’ts Spatial data analytics Geo Batch Near Real-Time Basic Geo Operations Workflow Composition Geo Streams Real-Time Advanced Geo Op. Unattended Workflow
- 35. What’s next?
- 36. Spatial data analytics RFC ;)
- 37. Moltes gràcies! nom@bdigital.org mplanaguma@bdigital.org @djkram @bdigital
- 38. 17TH ~ 18th NOV 2014 MADRID (SPAIN)