Dominate your data with this cutting-edge data intelligence platform.
Databricks is a data and AI company
Databricks is a unified, open analytics platform for building, deploying, sharing, and maintaining enterprise-grade data, analytics, and AI solutions at scale. The Databricks Data Intelligence Platform integrates with cloud storage and security in your cloud account and manages and deploys cloud infrastructure on your behalf.
Databricks provides tools that help you connect your data sources to one platform to process, store, share, analyse, model and monetise datasets with solutions from BI to generative AI.
Databricks brings AI to your data to help you execute informed decision making
Run all your SQL and BI applications efficiently at scale, achieving up to 12 times better price and performance using your preferred tools.
Streamline your data streaming process to enable real-time analytics, machine learning, and applications all within a single platform.
Increase the productivity of your teams with built-in data quality testing and support for software development.
Databricks empowers businesses to deploy, manage, and iterate on machine learning models, accelerating the journey from data to AI.
Develop and deploy high-quality machine learning (ML) and Generative Artificial Intelligence (GenAI) applications.
Ensure compliance with industry regulations and safeguard your sensitive data throughout its lifecycle with Databricks’ robust data governance features.
Elevate your decision-making, streamline operations, and stay ahead of the competition with our comprehensive suite of data science services.
Simplify and accelerate your data and AI goals
The Databricks Data Intelligence platform empowers your entire organisation to leverage data and AI. It is built on a Data lakehouse, providing an open, unified base for data and governance, and is powered by a Data Intelligence Engine.
With the help of generative AI and lakehouse unification, Databricks powers a data intelligence engine that understands the unique semantics of your data. This enables the Databricks platform to optimise performance automatically and handle infrastructure tailored to your business needs.
Leveraging natural language makes the user experience more seamless and simple on Databricks. The Data Intelligence Engine is adept at understanding the language of your organisation, making the search and discovery of new data as effortless as posing a question to a colleague. Moreover, the process of developing new data and applications is expedited through natural language assistance, facilitating tasks such as code writing, error remediation, and finding answers.
Security and strong governance are paramount for Data and AI applications, particularly in the era of generative AI. Databricks offers a comprehensive MLOps and AI development solution that is rooted in our unified approach to governance and security. This empowers you to embark on all your AI initiatives, whether utilising APIs like OpenAI or developing custom models, without sacrificing data privacy and IP control.
Databricks presents unique selling points that stand at the forefront of innovation, offering unparalleled solutions and redefining the way organisations harness the potential of data analytics and machine learning.
Experience seamless integration and collaboration with our Unified Data Platform.
Break down data silos and bring together diverse data sources, enabling a holistic view of your business information.
Lakehouse combines the best features of data lakes and data warehouses. The combination of unified data management, schema enforcement, transactional capabilities, analytical optimisation and compelling solution for modern data-driven organisations.
It addresses many of the limitations and challenges associated with traditional data lakes and data warehouses, providing a more comprehensive and efficient platform for managing and analysing data at scale.
Databricks is designed to scale effortlessly from small prototypes to large-scale production deployments.
It leverages cloud infrastructure for elastic scaling and offers optimisations for performance-critical workloads, allowing users to process and analyse massive datasets with ease.
Databricks provides AutoML capabilities that automate various aspects of the machine learning workflow, including feature engineering, model selection, and hyperparameter tuning.
This helps data scientists accelerate the model development process and build high-quality models more efficiently.
Experience seamless integration and collaboration with our Unified Data Platform.
Break down data silos and bring together diverse data sources, enabling a holistic view of your business information.
Leveraging the robust Apache Spark open-source framework, Databricks enhances its capabilities with additional features and optimisations.
This augmentation simplifies the process of constructing and deploying scalable data pipelines and machine learning models.
Lakehouse combines the best features of data lakes and data warehouses. The combination of unified data management, schema enforcement, transactional capabilities, analytical optimisation and compelling solution for modern data-driven organisations.
It addresses many of the limitations and challenges associated with traditional data lakes and data warehouses, providing a more comprehensive and efficient platform for managing and analysing data at scale.
Databricks offers collaborative features such as notebooks, version control, and project management tools that enable data teams to work together efficiently.
It also provides built-in support for popular programming languages like Python, R, and SQL, making it accessible to a wide range of users.
Databricks is designed to scale effortlessly from small prototypes to large-scale production deployments.
It leverages cloud infrastructure for elastic scaling and offers optimisations for performance-critical workloads, allowing users to process and analyse massive datasets with ease.
Databricks provides AutoML capabilities that automate various aspects of the machine learning workflow, including feature engineering, model selection, and hyperparameter tuning.
This helps data scientists accelerate the model development process and build high-quality models more efficiently.
Databricks prioritises security and compliance by offering features such as data encryption, access controls, and audit logging.
It also supports integration with identity providers and compliance frameworks, making it suitable for organisations with strict security requirements.