Description
At Iggy we provide easy access to hundreds of geospatial features to help companies make sense of ‘place’. We believe that incorporating ‘place’ into data science and machine learning pipelines can have a huge impact on predictive capabilities in a wide range of fields such as travel, real estate, healthcare, logistics and many more. Traditionally this data was accessible in a tabular form, but recently we have been experimenting with converting our tabular data into a graph representation, and applying graph machine learning to build derived products. This allows us to leverage the power of graphs and to more effectively model the relationships between different entities in our data. In this talk we will present: 1. What is geospatial data? 2. Why are we interested in graph representations of geospatial data? 3. What do our graph representations look like? 4. How are we applying graph machine learning? 5. What are some use cases and derived products that we are building using graph machine learning? Connect with us: Website: https://databricks.com Facebook: https://www.facebook.com/databricksinc Twitter: https://twitter.com/databricks LinkedIn: https://www.linkedin.com/company/…
Description from YouTube. Full content on the video page.
More from Databricks
NewsGovern MCP servers in Databricks #databricks #mcp #aigovernance
Databricks Unity AI Gateway now governs MCP servers, centralizing their management alongside built-in foundation models and LLMs. This integration allows for easier governance and orchestration of various AI components and agents within Databricks.
NewsHow Suntory Turns Data into Faster Decisions with Databricks
Suntory uses Databricks to integrate diverse datasets, including internal sales, macroeconomic factors, and consumer behavior, into "Project Brain" for faster decision-making and product launches. The company also implements an all-employee upskilling program, "Manabi no Michi," to empower its workforce to leverage AI for improved performance and efficiency.
NewsAIA Group x Databricks: Turning Regulated Data into Real-Time Intelligence
AIA Group leverages Databricks to manage regulated data across 18 markets, addressing challenges like data residency and varying tech maturity with features like Unity Catalog for governance. The platform enables real-time intelligence for investment decisions, fraud detection, and personalized agent coaching, with future plans for conversational analytics and autonomous AI.
TutorialsConnect Google Sheets to Databricks
The Databricks Google Sheets add-in allows users to explore, import, and refresh governed data from the Databricks Lakehouse directly within Google Sheets. It demonstrates how to browse Unity Catalog, select tables or metric views, apply filters, schedule data refreshes, and use direct SQL queries with parameters.
NewsNo More Table Locks for Multi Statement Transactions #databricks #dataengineering #sql
Databricks now supports multi-table transactions, allowing changes to multiple tables within a single atomic transaction that rolls back all changes if any part fails. This feature, managed by Unity Catalog, prevents table locking during updates and supports up to 100 tables per transaction using a simple "BEGIN ATOMIC...END" syntax.
NewsMay 2026 Databricks Updates: No Code ETL, New GPUs and Death of the Dashboard
Databricks announced several updates including AI Prep Search for document chunking and vector database preparation, SQL vector functions for embedding mathematics, and the general availability of multi-table transactions. They also introduced Lakeflow Designer for visual, no-code data pipeline creation and updated their serverless GPU offerings to include H100s.