How we can help:
- Accelerate time-to-value for new Databricks implementations: Whether you’re just beginning with Databricks or transitioning from legacy on-premises data environments like Hadoop, our platform-centric methodology expedites the realisation of Databricks’ benefits.
- Address governance for established Databricks users: For seasoned Databricks customers, implementing a data mesh with Sourced can resolve governance issues, enabling scalability, rapid access to data products and the availability of high-quality data for ML use cases.
- Cut Databricks costs: Unmonitored, Databricks costs can spiral due to misconfigurations or inefficient use. Our FinOps specialists identify cost-saving opportunities, reducing infrastructure expenses by over 90%.
- Scale ML operations efficiently: While many enterprises succeed in deploying initial ML models, scaling them is often a challenge. Our platform approach integrates security, governance, compliance, observability and best practices, empowering your data science teams to scale ML models more effectively and maximise ROI.