Databricks

Databricks is a unified data platform that offers integrated solutions in fields such as big data, artificial intelligence (AI), and machine learning (ML). It was founded in 2013 in San Francisco by Ali Ghodsi, Matei Zaharia, Reynold Xin, Patrick Wendell, Andy Konwinski, Ion Stoica, and Arsalan Tavakoli. The company is built on Apache Spark, an open-source big data processing engine developed by its founders.

Data Intelligence Platform

Databricks provides a Data Intelligence Platform that enables organizations to manage all data-related processes through a centralized infrastructure by combining diverse data sources, AI functions, and governance systems. This platform is based on the architecture the company calls a “Lakehouse,” which merges data warehouse and data lake paradigms to offer both flexibility and structural consistency.

Business Intelligence and AI/BI Solutions

AI/BI (Artificial Intelligence / Business Intelligence) solutions are tools that enhance business intelligence with technologies such as natural language processing (NLP) and generative AI. The platform’s AI/BI Genie enables users to query data using natural language. With AI/BI Dashboards, business teams can create interactive visualizations and reports. Databricks SQL provides a lakehouse-based, self-optimizing data warehouse solution.

Mosaic AI and Agent Systems

Mosaic AI is a platform developed by Databricks for building generative AI models and intelligent agents. Developers can train, test, and deploy large language models (LLMs) on proprietary data. Mosaic AI includes components such as AI Gateway, Agent Framework, Vector Search, Model Serving, and Agent Evaluation. These tools enable the creation of secure, controlled, and customizable generative AI applications.

Data Governance: Unity Catalog

Unity Catalog is the unified and open data governance solution offered by Databricks. It allows centralized management of structured data (e.g., tables), unstructured data (e.g., documents), ML models, notebooks, dashboards, and files. With Unity Catalog, users can enforce fine-grained access control, track data lineage, and audit user activities.

Open Source Data Sharing: Delta Sharing

Delta Sharing is an open-source data-sharing protocol developed by Databricks in collaboration with the Linux Foundation. It allows live data sharing across different cloud providers and data platforms without the need for replication. Delta Sharing reduces costs and increases efficiency while supporting the distribution of datasets, AI models, and notebooks via the Databricks Marketplace.

Executive Use

Databricks provides tools that facilitate data-driven decision-making for senior executives. Its unified platform eliminates data silos, enforces centralized governance and security policies, and enables organization-wide scalability of generative AI applications. The company reports an average return on investment (ROI) of 482%.

Industrial Applications and Users

Databricks solutions are used in a wide range of industries, including healthcare, manufacturing, finance, energy, media, and the public sector. Organizations such as Rolls-Royce, Adobe, Shell, DuPont, Tufts Medicine, JetBlue, Condé Nast, Block, and HSBC use Databricks as part of their data management and AI strategies.

Future Outlook

Databricks envisions becoming a leading platform in a digital ecosystem where data intelligence and generative AI applications are increasingly widespread. With its “Data + AI” approach, the company aims to democratize AI across all organizations. Future developments are expected to include natural language-powered query systems, agent-based generative models, industry-specific AI solutions, and enhanced open data-sharing infrastructures.

The company’s upcoming areas of focus include:

• Secure and customized integration of open-source LLMs with enterprise data
• Increased automation through the integration of AI agents into business processes
• Enhanced data security, regulatory compliance (e.g., GDPR), and transparency via adaptive governance systems
• Expansion of multi-cloud architectures for cross-platform interoperability
• Development of generative AI-based vertical solutions in strategic sectors such as education, healthcare, energy, public services, and finance.