Case Studies
Learn how our customers benefit from dlt
How do data engineers use dlt? Dive into the narratives below to see how data engineering teams solve their problems with dlt.
How insurance company Dentolo democratizes data access using dlt
How Dentolo transformed its data ingestion process by adopting dlt empowering the team with a composable data stack and democratizing data access across the organization.
PostHog leverages dlt to offer their users a scalable and inexpensive one-click data warehouse
How PostHog adopted dlt to build a scalable, customizable data warehouse that seamlessly handles large datasets, empowering their team to deliver a flexible and high-performing solution for users.
How Harness transformed 14 data pipelines in 14 days
How Harness chooses dlt + sqlmesh to create an end-to-end next generation data platform.
Fintech Taktile builds a compliant data platform with Snowflake + dlt
How Taktile uses dlt + snowflake for custom data needs and empowers all software engineers.
The current machine learning revolution has been enabled by the Cambrian explosion of Python open-source tools that have become so accessible that a wide range of practitioners can use them. As a simple-to-use Python library, dlt is the first tool that this new wave of people can use. By leveraging this library, we can extend the machine learning revolution into enterprise data.
- Julien Chaumond
- CTO/Co-Founder at Hugging Face