If we didn’t have Immuta, then Billie’s expansion as a business wouldn’t be possible. I’m not sure how we could do it without Immuta.
Product Overview
Immuta Data
Immuta Data
Security Platform
Immuta's Data Security Platform delivers data access and security at scale. Immuta discovers, secures, and monitors an organization's data to ensure that users have access to the right data at the right time – as long as they have the rights.
Self-guided Demo
Igor Chtivelband
Co-Founder and VP of Data
We're looking at ways that we can enable more sensitive use cases by using Immuta, which is a self-service data access and privacy control layer on top of that data lake.
Rohan Dhupelia
Data Platform Manager
Databricks opens up many opportunities for self-service data analytics, data science, and enterprise reporting. Paired with Immuta, we can make all our data available to all types of business analysts, data scientists and data engineers.
Ajay Sahu
Director of Enterprise Data Management
We look forward to helping bring Immuta’s cloud data access control capabilities to more joint customers as they’re building their future data and analytics stack on the lakehouse platform.
Ali Ghodsi
CEO and Co-Founder
With Immuta, we’ve been able to streamline data science and engineering teamwork, dynamically adapt in real time, and accelerate productivity.
Halim Abbas
Chief AI Officer
Immuta’s automated, integrated approach to data access control brings fine-grained data security to Snowflake customers who deal with large amounts of sensitive data.
Tariek Dwiek
Director of Technology Alliances
By incorporating Immuta’s data security and privacy capabilities, we have enhanced the overall strength and security of the platform.
Walid Mehanna
Head of Data & Analytics
Immuta is the go-to technology to implement our vision of an internal ‘Data & Analytics Marketplace’, enabling full transparency on the relevant data assets with secure and compliant data access.
David Abrahams
Data Leader
Databricks gives us scale and speed, Immuta gives us trust and privacy.
Slava Frid
CTO
ABAC Explainer
How Attribute-Based Access Control Works
Data teams are moving from RBAC to ABAC to make building and applying data policies simpler and more scalable. Instead of roles, ABAC uses tags - or metadata - to make run-time decisions on what data a user can see. But, ABAC is more than just tagging.
ABAC 101
Feature Highlights
Built for how data teams work with data policies
Our data security platform empowers data teams to manage data policies more efficiently. That means making really hard things possible and simpler things automated.
Feature Highlights
Built for how data teams work with data policies
Our platform empowers data teams to manage data policies more efficiently. That means making really hard things possible and simpler things automated.
Feature Highlights
Built for how data teams work with data policies
Our platform empowers data teams to manage data policies more efficiently. That means making really hard things possible and simpler things automated.
Feature Highlights
Built for how data teams work with data policies
Our platform empowers data teams to manage data policies more efficiently. That means making really hard things possible and simpler things automated.
100x Faster Data Access
Streamline data access flows and approvals, going from months to seconds.
75x Fewer Data Policies
Reduce the number of policies required with Attribute-Based Access Control.
Improved Data Security & Compliance
Prove compliant data use with company rules and external regulations.
What is data security management?
Data security management is the collection of processes and techniques meant to protect data against unauthorized access, use, and corruption. This can include the management of measures such as data access control, data governance, compliance, and other methods for ensuring the security and privacy of sensitive information.
What is data access control?
Data access control is used to protect a company’s data by allowing access to authorized database users and restricting access to unauthorized users. If used correctly, it offers a variety of business benefits including data governance, compliance, data-rich application development, increased efficiency of data analytics, and more value derived from sensitive data.
What is the definition of dynamic access control?
Dynamic data access control refers to permitting or restricting data access based on context-aware attributes. As opposed to static access control methods, like role-based access control (RBAC), dynamic data access controls make access decisions at query time based on factors like geography, data owner, and intended usage purpose. Dynamic data access control, such as attribute-based or purpose-based access control, is a more scalable and flexible approach to protecting data because it ensures that only the right people can access the right data at the right time.
What are the steps for attribute-based access control implementation?
Attribute-based access control makes dynamic access decisions based on characteristics about the user, object, environment, and intended action. Therefore, the first step in implementing ABAC is to connect your data catalog, business applications, or IAM system to your access control tool so that policies can leverage user metadata. This way, updates to identity management systems will be automatically reflected in policy enforcement with no additional effort required by data teams. Another important step in ABAC implementation is to establish a system for data discovery, classification, and tagging, so that as new data enters the network, sensitive information can be easily identified and tagged for appropriate policy enforcement. With these systems in place, data teams can author policies in plain language that take the attributes associated with users and data into account, enabling flexible, dynamic access decisions to be made at query runtime.
What should I look for in data masking technology?
Effective data masking technology must fulfill a few distinct functions. First, it should enable the identification of sensitive data so it can be masked appropriately. It should also consider referential integrity, data access and governance measures, and ensure repeatability and the ability to scale. Finally, data masking technologies that enable privacy enhancing technologies (PETs) offer advanced protection for sensitive data. By fulfilling these functions, data masking technology can work to proactively protect your sensitive data from any sort of breach, leak, or misuse without getting in the way of data consumers’ needs.
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