Databricks, the lakehouse company, is launching Databricks Model Serving, a solution aiming to streamline the management and scaling of production machine learning (ML) within the Databricks Lakehouse ...

Databricks announced Genie ZeroOps, an autonomous background agent designed to monitor production data and AI workloads, investigate issues, and suggest fixes that teams can verify before applying.

Omar Khawaja argues CISOs should be skilled at talent development, operating models, change management and decision support. The data analytics platform provider has been using ML to drive functions ...

Databricks Inc. opens its Data + AI Summit today with the announcement that it will release the entirety of its Delta Lake storage framework to open-source under the oversight of the Linux Foundation.

Snowflake and Databricks are surely similar companies. While each positions itself a bit differently, both provide data storage, processing and governance in a cloud context. Both are holding customer ...

Organizations can improve performance and reduce costs by replacing the stock Databricks Runtime for Machine Learning libraries with versions optimized by Intel. Here’s how to get started. Getting the ...

Databricks is pitching a fix for what it sees as the growing operations mess in enterprise AI. With the launch of Genie ZeroOps, unveiled at its Data + AI Summit, the company is targeting a problem ...

Data analytics developer Databricks Inc. today announced the general availability of Databricks Model Serving, a serverless real-time inferencing service that deploys real-time machine learning models ...

SAN FRANCISCO, June 23, 2022 (GLOBE NEWSWIRE) -- Tecton, the enterprise feature store company, today announced a partnership with Databricks, the Data and AI Company and pioneer of the data lakehouse ...

Tecton, the enterprise feature store company, is partnering with Databricks, the Data and AI Company, to help organizations build and automate their machine learning (ML) feature pipelines from ...

Traditional SIEM platforms often underperform due to high costs, inflexible schemas and limited scalability. These barriers make it hard to use advanced analytics, keep historical data and integrate ...