Product Overview

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
 

What customers say

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.

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

Know what sensitive data you have

Immuta automatically scans cloud data sources, detects sensitive data, and generates standard tagging across multiple compute platforms, reducing risk and improving data utility.

Write policies and enforce them

Collaborate as a team to build PBAC, ABAC, and RBAC data policies that dictate fine-grained data security (row, column, cell) and employ advanced data masking techniques for the utmost privacy.

Prove compliance

Our data access platform allows you to easily track who can access what data, policy changes, and user queries for audit purposes, as well as help determine risk profile for sensitive data and associated policies.

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.

Scan & classify

Connect to Immuta in minutes and begin scanning your data, applying standard tags, and using over 65+ pre-built classifiers. You can also leverage metadata from Data Catalogs that Immuta integrates with such as Collibra or Alation.

Write policies

Easily author and implement policies in plain language – or using policy-as-code – for both transparency and flexibility. Immuta is designed to work with and streamline your existing tools and processes.

Mask data

Enforce policies at query runtime using techniques like hashing, without writing code or copying data.

Audit

Automatically log all actions and quickly run reports to prove compliant data use and investigate incidents.

Why Immuta

100x Faster Data Access
100x Faster Data Access

Streamline data access flows and approvals, going from months to seconds.

75x Fewer Data Policies
75x Fewer Data Policies

Reduce the number of policies required with Attribute-Based Access Control.

Improved Data Security & Compliance
Improved Data Security & Compliance

Prove compliant data use with company rules and external regulations.

Frequently Asked Questions

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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