Secure your big data and ML workflows with a unified approach to data security.
Databricks employs a Defense in Depth security model to provide the most advanced protection for your data, AI and Apache SparkTM workflows at every layer.
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AWS and Azure data centers are frequently audited and comply with a comprehensive set of frameworks including ISO 27001, SOC 1, SOC 2, SOC 3, PCI DSS.
Additionally, AWS and Azure physical data centers are located in non-disclosed locations and have stringent physical access controls in place to ensure that no unauthorized access is permitted, including biometric access controls and twenty-four hour security guards and video surveillance.
Click over each layer of our security model to learn more
Hover over each layer of our security model to learn more
Many companies today operate on disjointed homegrown DIY (do-it-yourself) data and AI platforms. Databricks Unified Analytics Platform brings data engineering and data science teams together giving the data scientist the agility they want while providing data engineers a consistent, secure and reliable toolset with no patching or configuration issues.
Databricks lets both data engineering and data science teams work together in a single shared workspace. Databricks interactive notebooks contain runnable code, visualizations, narrative text and can be shared by multiple teams with commenting and versioning. Not only does this enhance collaboration and but is a single interface to control, track and audit access to data.
Learn how to securely access external data sources from Databricks for AWS >