Databricks Code Promo

Databricks is a unified data processing and artificial intelligence platform that enables companies to manage and analyse large quantities of data. It combines data processing with analysis and machine learning tools, facilitating collaboration between data science and engineering teams. Databricks offers environments based on Apache Spark, enabling fast and scalable data processing.

With advanced visualisation and integration capabilities, the platform helps businesses to extract meaningful insights from their data. In short, Databricks is a powerful tool for companies looking to optimise their data management and accelerate their AI projects.

Intelligent. Simple. Private.

The Databricks Data Intelligence Platform allows your entire organization to use data and AI. It’s built on a lakehouse to provide an open, unified foundation for all data and governance, and is powered by a Data Intelligence Engine that understands the uniqueness of your data. The winners in every industry will be data and AI companies. From ETL to data warehousing to generative AI, Databricks helps you simplify and accelerate your data and AI goals.

Intelligent:

Databricks combines generative AI with the unification benefits of a lakehouse to power a Data Intelligence Engine that understands the unique semantics of your data. This allows the Databricks Platform to automatically optimize performance and manage infrastructure in ways unique to your business.

Simple:

Natural language substantially simplifies the user experience on Databricks. The Data Intelligence Engine understands your organization’s language, so search and discovery of new data is as easy as asking a question like you would to a coworker. Additionally, developing new data and applications is accelerated through natural language assistance to write code, remediate errors and find answers.

Private:

Data and AI applications require strong governance and security, especially with the advent of generative AI. Databricks provides an end-to-end MLOps and AI development solution that’s built upon our unified approach to governance and security. You’re able to pursue all your AI initiatives — from using APIs like OpenAI to custom-built models — without compromising data privacy and IP control.

AI - Build better AI with a data-centric approach:

Great models are built with great data. With Databricks, lineage, quality, control and data privacy are maintained across the entire AI workflow, powering a complete set of tools to deliver any AI use case.

• Create, tune and deploy your own generative AI models
• Automate experiment tracking and governance
• Deploy and monitor models at scale

Governance - Unify governance for data, analytics and AI:

Maintain a compliant, end-to-end view of your data estate with a single model of data governance for all your structured and unstructured data. Discover insights rooted in the characteristics, people and priorities of your business.

• Context-aware natural language search and discovery
• AI-powered monitoring and observability
• Single permission model for data + AI

Warehousing - The best data warehouse is a lakehouse:

Achieve 12x better price/performance for SQL and BI workloads by moving from legacy cloud data warehouses to a lakehouse.

• Serverless for simplified management
• AI-optimized query execution
• Open formats and APIs to avoid lock-in

ETL - Intelligent data processing for batch and real time:

Implement a single solution for all of your ETL use cases that automatically adapts to help ensure data quality.

• Simple workflow authoring for batch and streaming
• End-to-end pipeline monitoring
• Hands-off reliability and optimization at scale

Data Sharing - Open data sharing:

The first open approach to secure data sharing means you can easily share live data sets, models, dashboards and notebooks to collaborate with anyone on any platform.

• No proprietary formats or expensive replication
• No complicated ETL
• Monetize sharing with the Databricks Marketplace

Orchestration - Manage pipelines to business requirements:

Optimize data pipeline execution to deadlines and budget requirements.

• Intelligent selection of compute type
• Workload-specific autoscaling
• Automatic remediation of errors