Search: “databricks”

Databricks introduces database branching capabilities through Lakebase, enabling developers to create isolated database branches for parallel development and testing without affecting production envir

This Databricks resource discusses how pharmaceutical companies can use analytics to optimize their product launch strategy, focusing on accelerating critical decision-making during the crucial first

This Databricks resource explains how to use SQL alerts to automate the monitoring of data quality and key performance indicators (KPIs), enabling automated detection and notification of anomalies or

This Databricks guide demonstrates how to implement real-time fraud detection systems by leveraging Spark Real-Time Mode and Lakebase to process and analyze streaming data for identifying fraudulent t

This article is the second installment in a series exploring Lakebase, Databricks' data management solution, providing behind-the-scenes insights into its architecture, capabilities, or integration wi

PipelineIQ is a Databricks solution that leverages data analytics and AI to provide predictive sales intelligence, enabling sales teams to forecast pipeline outcomes and identify actionable opportunit

Databricks announced expanded interoperability capabilities for Unity Catalog through open APIs, enabling third-party applications and platforms to integrate with and access Unity Catalog's data gover

This article likely explores how Databricks' unified analytics platform enables energy traders to process and analyze market data in real-time, supporting faster decision-making and risk management in

Databricks' Lakebase architecture optimizes PostgreSQL write performance by achieving 5x faster speeds through architectural innovations. The approach likely leverages optimizations such as improved b

Databricks has implemented catalog federation capabilities that enable Unity Catalog to interoperate with Google BigQuery, allowing users to access and manage BigQuery datasets through the Unity Catal

Operational databases are designed to manage and power real-time transactions by handling high-throughput Online Transaction Processing (OLTP) workloads. They differ significantly from data warehouses

This guide from Databricks covers data transformation techniques and best practices essential for preparing data for AI/ML projects, addressing workflows that both data engineers and data scientists e

This Databricks resource explains how to implement customer-managed keys (CMK) for encryption in Lakebase Postgres, enabling users to control their own encryption keys rather than relying on provider-

Banks face challenges implementing AI not due to lack of AI technology, but rather due to fragmented, siloed data platforms that prevent effective data integration and accessibility. The article argue

Databricks AI Gateway provides a secure mechanism for connecting AI agents to external Model Context Protocol (MCP) servers, enabling agents to access external tools and data sources without exposing

Databricks explores how agentic AI systems can reason over both structured data (such as tables and databases) and unstructured data (such as documents and text) to answer complex business questions.

Since our initial announcement, we have started onboarding beta design partners. - Connect your Lakebase data - Build an application - Deploy to your Databricks account Reach out to your Replit/Databr

The article describes a method for creating a scalable AI‑agent orchestrator on Databricks that relies solely on Lakebase Postgres. It explains how the database can handle coordination and task schedu

Feature Views is a Databricks capability that provides a standardized way to define, manage, and serve machine learning features across an organization. This feature enables data teams to create reusa

Agentic marketing leverages AI agents to automate marketing tasks, and this approach requires a robust data foundation as its core component. Databricks discusses how organizations need unified data p

Databricks describes contextual policies in Omnigent, a framework that leverages session state to implement more effective governance and control mechanisms for AI agents. By maintaining and utilizing

Databricks introduces Vibe Data Modeling, a new approach to data modeling designed specifically for lakehouse architectures that aims to simplify and improve how organizations structure and manage dat

This article outlines three key questions organizations should address when scaling AI initiatives from pilot projects to production impact. Based on the Databricks focus, it likely covers questions r

This Databricks article discusses advanced forecasting techniques and tools designed to meet the rapid decision-making demands of contemporary retail operations. It likely covers how modern retailers

This Databricks resource explains how to implement granular usage attribution in dbt data transformation pipelines using query tags, enabling detailed tracking of compute resources and costs at a fine

This article discusses Databricks' evolution of database architecture, tracing the progression from monolithic database systems to Lakebase and then to LTAP (Lakehouse Transaction Processing), emphasi

AVL, a leading automotive testing company, modernized its measurement data analytics by adopting Databricks' Lakehouse architecture to replace traditional test bench data processing systems. The imple

Daikin Applied Americas leverages Databricks' Genie Code to build and maintain data pipelines at scale with consistency and efficiency. The solution enables the organization to streamline data pipelin

This Databricks blog post explores how organizations can leverage their existing data assets to find answers to business questions without requiring additional data collection or external sources. The

This guide from Databricks covers the fundamentals of agentic systems and AI agents, including their architecture, capabilities, and how they differ from traditional AI applications. It likely explain

This article from Databricks outlines ten artificial intelligence solutions that businesses can implement to accelerate growth and improve operational efficiency. The piece likely covers practical AI

Databricks offers an AI serving platform designed to flexibly accommodate different machine learning models and their specific requirements. The platform likely provides features for deploying, scalin

This Databricks blog post discusses how organizations can scale their AI initiatives by developing data fluency—the ability to effectively understand, manage, and leverage data across the enterprise.

This Databricks blog post outlines a strategic framework for enterprises to align their data initiatives with measurable business outcomes. It likely covers best practices for developing a comprehensi

This article explores how Databricks' Genie product and AI agents can automate and improve the processing of maintenance reports for renewable energy installations, specifically solar and wind facilit

This Databricks guide provides financial services leaders with essential information and strategies for attending or engaging with the Data + AI Summit 2026, covering industry-specific insights on lev

Databricks presents Instructed-Retriever-1, a system that achieves 3x faster search performance through parallel test-time scaling techniques. The approach optimizes retrieval operations by executing

This Databricks article explores Apache Spark's real-time mode capabilities for gaming applications, specifically focusing on how to implement efficient real-time sessionization to group and analyze p

This Databricks resource presents a framework for assessing and advancing an organization's AI governance capabilities through a maturity model structure. It likely provides a matrix for evaluating cu

This Databricks resource provides a comprehensive framework for implementing data governance architecture in contemporary organizations, covering the essential components, best practices, and structur

Query Tags is a Databricks feature that adds contextual metadata to warehouse queries, enabling better tracking, organization, and management of query workloads. This capability allows users to label

This Databricks article challenges common misconceptions about data layout optimization strategies, comparing Liquid Clustering with traditional partitioning approaches. It examines eight specific myt

Enterprise leaders are implementing AI agents across their organizations through strategies that address deployment, governance, and integration challenges. The article from Databricks likely covers b

Unity Catalog, Databricks' open governance solution, integrates with Apache Iceberg to provide unified metadata management, access controls, and data lineage across data lakes and warehouses. This int

Databricks announced the launch of Change Data Feed (CDF) for Lakebase, a feature that captures and tracks data modifications (inserts, updates, deletes) in real-time or batch processes. This capabili

This Databricks blog post provides guidance on optimizing business intelligence serving infrastructure for both performance and total cost of ownership. It likely covers best practices for configuring