Aditya Paliwal
Data Engineer, Datashift
Leuven, Belgium
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Aditya Paliwal, Data Scientist.
Main fields of expertise are Geospatial research, data engineering & CI/CD , Predictive Maintenance and Retrieval Augmented Generation (LLMs)
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How AI and geospatial insights are driving business growth
Ever wondered what kind of impact geospatial data can have on your business? The answer: “A big one”! Most businesses have a geolocation component and when used effectively, geospatial data, combined with best data practices can drive growth, reduce costs, and open up new strategic opportunities.
Think of smarter customer segmentation for dynamic marketing and pricing, optimized delivery routes, or finding the perfect location for your next store or warehouse. Geographical data plays its role in almost all business sectors. In this session, we’ll walk through the full lifecycle of geospatial data—from storage/collection using PostGIS in databases to analysis using GeoPandas to visualization using QGIS & python libraries with real-world applications. You will also learn how to harvest the power of machine learning to create insights from geospatial data
Whether you're a business leader looking to create value or a technical expert wanting to learn geospatial best practices, this session offers practical strategies and real-world examples to help you make the most of geospatial data.
Key Take-aways:
Understanding geolocation data and learning how to implement geospatial solutions using best practices.
Developing a strategy for geospatial value creation
Geo-Intelligence: Unlocking Insights Through Open-Source Geospatial Analytics
Most businesses have a geolocation component, think of tracking a runners club to show progress, optimized delivery routes or finding the perfect location for your next store. When implemented effectively, geospatial data can drive growth and open up new strategic opportunities.
The talk will walk you through the full lifecycle of geospatial data developments with open-source tools—from preprocessing GPS signals with Kalman filters to SQL processing using PostGIS in PostgreSQL databases. You will learn how to analyze and transform data in Python using GeoPandas, the geospatial extension of Pandas. When the data is ready, you’ll see how to visualize geospatial data using Python libraries such as Folium and the open-source tool QGIS. You will also learn how to use unsupervised machine learning models to segment geospatial time-series and classify, for example, the types of movement.
In the demo, we will show step-by-step a geospatial pipeline that transforms a the GPS trace of a runner & cyclist into processed insights. We’ll learn how to visualize and manipulate geospatial data in QGIS.
How AI and geospatial insights are driving business growth
Ever wondered what kind of impact geospatial data can have on your business? The answer: “A big one!". Most businesses have a geolocation component and when used effectively, geospatial data, combined with best data practices can drive growth, reduce costs, and open up new strategic opportunities.
Think of smarter customer segmentation for dynamic marketing and pricing, optimized delivery routes, or finding the perfect location for your next store or warehouse. Geographical data plays its role in almost all business sectors. In this session, we’ll walk through the full lifecycle of geospatial data—from storage/collection using PostGIS in databases to analysis using GeoPandas to visualization using QGIS & python libraries with real-world applications. You will also learn how to harvest the power of machine learning to create insights from geospatial data
Whether you're a business leader looking to create value or a technical expert wanting to learn geospatial best practices, this session offers practical strategies and real-world examples to help you make the most of geospatial data.
Key Take-aways:
Understanding geolocation data and learning how to implement geospatial solutions using best practices.
Developing a strategy for geospatial value creation
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