Knowledge catalogue
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
Databricks' lakebase architecture incorporates design principles and mechanisms to maintain resilience and availability when cloud infrastructure failures occur. The architecture likely employs redund
This article from Databricks discusses strategies and best practices for deploying large language models in production environments at scale while maintaining reliability and performance. It likely co
This Databricks blog post likely examines the prerequisites and preparedness required for telecommunications companies to successfully implement and deploy AI solutions. It probable covers organizatio
Octopus Energy reduced margin data engineering costs by 50x through scaling improvements implemented on the Databricks platform for MHHS (Metering, Half-hourly Settlement) operations. The case study d
This Databricks article discusses how organizations can leverage data and analytics to transition from simply tracking and reporting carbon emissions to making strategic decarbonization decisions. It
This Databricks blog post discusses the evolution from descriptive analytics (analyzing past events) to predictive analytics (forecasting future outcomes), likely exploring how modern data platforms e
This Databricks blog post discusses strategies for implementing personalization in media products after their initial development, likely covering how to leverage data and AI technologies to deliver c
Unity Catalog is Databricks' centralized governance solution that enables organizations to manage and control AI agents at scale by providing features for access control, lineage tracking, and complia
Databricks discusses how artificial intelligence can help telecommunications CFOs optimize capital expenditure decisions for network infrastructure by enabling data-driven analysis and predictive mode
Lakebase, a Databricks solution, enables organizations to create integrated marketing campaigns by leveraging data lakehouse capabilities to unify customer data and reduce marketing costs. The platfor
Unity AI Gateway Guardrails is a Databricks feature designed to protect AI workloads by implementing safety measures and policy controls within the Unity Catalog framework. The tool enables organizati
Databricks introduced AI spend controls as part of its Unity AI Gateway, enabling organizations to monitor, manage, and optimize costs associated with AI model usage and API calls. The feature likely
Unity Catalog is a Databricks governance solution that helps secure AI agent actions by managing access controls and permissions across agent operations. It prevents unauthorized or 'rogue' AI behavio
This Databricks blog post likely discusses how modern data platforms and analytics tools should enable organizations to quickly extract insights and answer business questions from their commercial dat
Databricks has released general availability for attribute-based access control (ABAC) features in Unity Catalog, including row filtering and column masking policies that dynamically restrict data acc
Databricks announced the general availability of Catalog Commits, a feature that integrates open table formats with open catalog systems to enable versioning and tracking of catalog-level changes. Thi
Databricks explores how lakehouse architecture enables sports organizations to process and analyze player tracking data at scale, converting raw motion capture and sensor information into actionable c
This Databricks resource examines retail markdown optimization strategies, contrasting reactive markdown approaches (responding to inventory issues after they occur) with proactive markdown strategies
This article describes a project using Databricks technology to convert unstructured archival documents into a searchable database to facilitate groundwater research and discovery. The work likely dem
The MCP Marketplace enables agentic applications to access real-time intelligence and data through a centralized platform of Model Context Protocol integrations. Databricks has launched this marketpla
Databricks' Genie is an AI-powered data agent designed to enable natural language interactions with data, allowing users to query, analyze, and generate insights without requiring SQL or coding expert
MemAlign is a technique used within Databricks' Genie code environment to enhance the evaluation and benchmarking of traditional machine learning models by optimizing memory alignment. This approach l
This Databricks article examines how distributed systems architectures need to be redesigned for serverless computing environments, addressing the unique performance and reliability challenges that ar
This Databricks blog post likely discusses how predictive analytics and machine learning can improve insurance payouts and risk assessment in volatile market conditions. The article probably covers te
This Databricks blog post discusses how organizations can achieve AI scalability through unified infrastructure and organizational alignment, emphasizing the importance of consolidating teams, platfor
This Databricks article discusses the gap between the readiness of AI agent technology and the organizational and technical architectures needed to deploy them effectively. It likely addresses infrast
This Databricks blog post introduces sketch functions that enable approximate query results with quantifiable accuracy bounds, allowing organizations to make exact decisions based on approximate analy
Companies that have achieved success with AI implementations prioritized building a robust data foundation and infrastructure before deploying AI models. Databricks emphasizes that a well-constructed
This Databricks blog post discusses modern approaches to SQL-based Extract, Transform, Load (ETL) processes designed for contemporary data platforms, likely covering how SQL ETL tools and practices ar
This Databricks blog post discusses how natural language processing can accelerate clinical data pipeline development, reducing implementation time from months to minutes. It covers techniques for ext
Databricks discusses how leading technology companies are using Lakebase to eliminate 'builder's tax'—the overhead and complexity costs associated with building and maintaining data infrastructure. Th
LangGuard's agentic workflow governance engine represents one of the first production deployments of Lakebase, Databricks' platform for managing AI agents. The deployment demonstrates how organization
This Databricks article examines whether Large Language Model agents can effectively optimize SQL join order, a critical query optimization problem in database systems. The analysis likely evaluates L
This Databricks blog post explains how to use Genie and Agent Bricks to streamline and automate document activation workflows. It likely covers how these tools can help organizations process, manage,
This guide from Databricks covers practical techniques and best practices for fine-tuning large language models, including methodologies for adapting pre-trained LLMs to specific tasks and domains. It
Databricks' Unity AI Gateway provides governance and control mechanisms for managing the proliferation of coding agents across enterprises, addressing challenges of oversight, security, and standardiz