Monte Carlo, the leading data + AI observability platform, today announced the launch of unstructured data monitoring, a new capability that enables organizations to ensure trust in their unstructured ...

Databricks is automatically compatible with all data types: structured, semi-structured, and even unstructured data ... Auto-scaling and auto-suspend, for example, help in stopping and starting ...

Cloud-based data intelligence ... engine project built by Databricks' founders—and uses its proprietary Lakehouse architecture to manage both structured and unstructured data.

For example, unstructured data could be as simple as MP3 file tags listing artist ... You want a data workflow engine that will feed data into a GraphRAG, a Snowflake table, a Databricks Delta format, ...

In insurance, for example, EXL will leverage Databricks to help insurance clients analyze ... In banking, EXL is working with Databricks to unlock the potential of unstructured transaction data, ...

tuning using only input data that companies already have – no labels required – while achieving results that outperform traditional fine-tuning on thousands of labeled examples. Databricks ...

With this new integration, organizations can safely harness the power of their structured and unstructured data anywhere with Databricks Data Intelligence Platform. Key capabilities include ...

Having the data together in Databricks is the beginning of creating the kinds of new analytics Frankle cites. While LLMs can make use of a pile of unstructured ... for example, a custom embedding ...

This enhancement is pivotal for organizations relying on Databricks to develop the ... head-on with APIs that manage structured and unstructured data, mitigating data security and privacy risks ...

Our services are designed to reduce costs, lower risks, and quickly increase ROI, transforming unstructured data into valuable business insights. Learn more about Adastra’s Databricks services ...