PAL4C Labs | From SQL to Ontology: Key Takeaways from the Palantir Foundry End-to-End Speedrun

This PAL4C Labs video reflects on the end-to-end speedrun in Palantir Foundry. It covers what the Ontology is, how the speedrun project comes together, and how this way of working compares with handling data through traditional SQL. What the Ontology does It links and joins datasets from different departments, and can union them even when each one uses a different schema. That gives people one shared workspace, instead of spending time rewriting SQL and reformatting data by hand. The speedrun project Three datasets come in: Bureau orders, Office Goods orders and consolidated customers. The order data is cleaned, joined with the customer data, and unioned into a new combined dataset. The Ontology is set up with properties and relationships that the app will use. A Workshop dashboard brings everything together for fulfillment teams, so they don’t have to switch between separate datasets or dashboards with conflicting schemas. That back-and-forth causes delays, especially at high volumes and after a merger. The biggest takeaway: compared with SQL With SQL, combining data like this can take close to a week: writing queries, cleaning and formatting data, and sometimes using Python or R before loading it into a database such as MySQL. Foundry’s low-code tools and the Ontology make the same work much faster and more efficient, including the more advanced features specific teams need. Built by PAL4C Labs, specialists in operational intelligence on Palantir Foundry and AIP.