1. Security remains the top concern for organizations migrating data warehouses to the cloud. How does ALTR’s integration with Databricks directly address these security concerns?
Security in the cloud isn’t just about locking down data or encrypting it at rest—it’s about knowing exactly what data you have, where it resides, and ensuring the right people have the appropriate level of access without overexposure. That’s where ALTR’s integration with Databricks becomes so powerful.
ALTR’s Data Security Platform connects directly to Databricks, allowing organizations to classify their data, identify sensitive information, and enforce granular security controls in a way that’s scalable, transparent and efficient. By leveraging pushdown policy enforcement, we enable security teams to apply controls dynamically, so that access is always aligned with business needs and compliance requirements. This means that data remains protected, whether it’s being used for analytics, AI, or machine learning, without disrupting operations or creating unnecessary bottlenecks. With ALTR, companies don’t have to choose between security and agility—they get both.
2. One of ALTR’s key differentiators is providing a unified view of data security across both Databricks and Snowflake. Why is this level of visibility so critical for enterprises, and how does it help organizations make better security decisions?
We’re seeing more and more enterprises using both Databricks and Snowflake, often within the same organization but for different use cases. Databricks is most often used for advanced Data Science, AI, and real-time processing, while Snowflake is widely used for structured data warehousing and BI reporting. This creates a major challenge for CISOs and data governance teams: how do you maintain visibility and enforce consistent security policies across both platforms?
That’s exactly what ALTR solves. With ALTR’s unified access policy, organizations get a single source of truth for their data security. They can see where all their sensitive data lives, initiate scans to discover new data, monitor and audit access policies across Databricks and Snowflake, and apply new policies with ease. Instead of managing security in silos, ALTR allows enterprises to take a unified approach, ensuring consistency, reducing operational complexity, and ultimately improving compliance and risk management.
3. Many security solutions require complex coding. ALTR’s no-code policy management aims to change that. How does this approach empower governance and security teams to enforce granular data controls without slowing down data operations?
Databricks is a platform designed for deep data science, AI, and machine learning—meaning companies are investing in highly skilled, highly paid data scientists and engineers to work with their data. These experts should be focused on extracting insights and driving business innovation, not writing access control policies or managing security configurations.
Traditionally, securing data in Databricks required writing complex SQL or Python-based access policies, which meant one of two things: either data scientists had to divert their time away from their core work, or security teams—who often don’t have deep coding expertise—struggled to implement and maintain those policies.
ALTR eliminates this challenge by providing a no-code interface that makes it simple to define and enforce granular access controls without writing a single line of code. Security and governance teams can apply, update, and manage policies with ease, ensuring that sensitive data is protected at all times without creating roadblocks for the teams who need to use that data. Plus, ALTR’s approach automatically generates documentation and audit trails, making compliance reporting far easier. By removing the complexity from security, we empower organizations to focus on what matters most—leveraging their data to drive value.
4. With Databricks investing heavily in its Unity Catalog for data governance, how does ALTR’s seamless integration accelerate an enterprise’s ability to secure and maximize the value of their Databricks data?
Databricks’ Unity Catalog is a huge step forward in simplifying governance across workloads, offering metadata management, access control, and lineage tracking. ALTR enhances this by integrating directly with Unity Catalog to provide advanced security and policy enforcement in a way that’s both seamless and scalable.
By leveraging Databricks’ native tagging framework, ALTR ensures that security policies are consistently applied across all metastores and workspaces. This gives organizations greater confidence in their security posture as they migrate data into Unity Catalog, knowing that sensitive information is automatically classified and protected. And because ALTR integrates directly into the governance workflow, security policies can evolve alongside data growth, ensuring that enterprises can maximize the value of their Databricks investment without introducing unnecessary risk.
5. As Databricks continues to evolve beyond a traditional data lakehouse into an AI and real-time analytics powerhouse, how do you see the role of data security changing, and where does ALTR fit into the future of AI governance?
As Databricks expands into AI, real-time analytics, and even broader enterprise use cases, data security is only going to become more critical. The challenge is that sensitive data is no longer just structured fields in a database—it’s embedded in unstructured formats, documents, images, and even machine learning training sets. The risk isn’t just about unauthorized access anymore; it’s about ensuring sensitive data doesn’t inadvertently end up in AI models or external integrations where control is lost.
This is where ALTR’s shift-left approach to data security comes in. We allow enterprises to identify and protect sensitive data before it ever enters Databricks AI pipelines. By enforcing policies at the ingestion stage, we ensure that only the right data is being used, preventing unintended exposure. And because AI governance is still an evolving challenge, ALTR provides the framework for organizations to adapt, applying fine-grained access controls that help them remain compliant and secure in an increasingly complex data landscape.
Ultimately, ALTR ensures that as enterprises scale their AI initiatives, they do so responsibly—without sacrificing security, privacy, or compliance.
