Immuta accelerates enterprise cloud data science adoption, reduces risk, and can lower costs

Immuta unveiled new features that can reduce the cost and risk of running data science programs in the cloud. The company also announced the creation of a new business unit dedicated to building managed cloud-services for its customers.

According to 451 Research’s Voice of the Enterprise AI/ML survey, over 50% of all organizations developing or deploying machine learning software highlighted public cloud as the favored development environment. However, as organizations move data science programs to the cloud, they often struggle to comply with stringent data privacy requirements, such as the EU General Data Protection Regulation (GDPR) and the Health Insurance Portability and Accountability Act (HIPAA), and therefore aren’t able to capitalize on the benefits of cloud economics.

Also, enterprises must create multiple copies of the data per policy, which in turn, also requires the creation of a separate Amazon Elastic MapReduce (EMR) cluster per user permission role – which increases cost and operational complexity.

The Immuta platform enables enterprises to operationalize data for their machine learning and advanced analytics programs while meeting policy and compliance requirements. This eliminates ad hoc policy enforcement that encumbers data owners and slows down the process of sharing data across teams and projects.

With its latest platform release, Immuta has eliminated the need for enterprises to create and prepare dedicated data copies in Amazon S3 for each policy that needs to be enforced. This allows multi-tenancy on a single Amazon EMR cluster through dynamic policy enforcement.

Additional new features of the Immuta platform include:

  • Batch workload support for Amazon EMR and Amazon S3: Data owners can now enforce complex data policy controls where storage and compute are separated to allow transient workloads on the cloud.
  • Project collaboration: Often, teams of data scientists need to collaborate, however struggle due to variations in access levels. Immuta solves this by equalizing all users to the same level from within a project, thereby providing data consistency for project collaborators.
  • Policy logic enhancements: Immuta expanded the range of policy enforcement controls in the latest release including support for:
    – Conditions (for everyone / everyone except) on row level and purpose restriction policies.
    – Conditional masking / cell-level security: ability to drive masking of a column based on the value in another column in that same row.
    – Combining Differential Privacy with other Immuta policy actions (i.e. mask, row level security).

“At Cognoa, we had always planned to migrate our data science operations to the cloud to accelerate innovation and scale data volume. This made Immuta an attractive option, as its platform supports dynamic and customizable privacy controls and sophisticated access roles for data science teams working in the cloud. For us, this means the ability to streamline our experimentation and work with improved agility, while at the same time maintaining compliance with industry guidelines such as HIPAA.”, said Halim Abbas, Chief AI Officer, Cognoa (Immuta Customer).

“We are seeing a growing trend towards cloud adoption for analytics workloads, especially within the most data-driven organizations. The cloud is well-suited for artificial intelligence (AI) model development and training use-cases, however, privacy and security issues continue to be of concern. As such, we anticipate growing interest in products and services that enable data-driven enterprises to leverage cloud for data science workloads while reducing the risk of accessing data across multiple environments through central management.”, said Matt Aslett, Research Vice President, 451 Research.

“To comply with data privacy controls, organizations spend enormous amounts of effort and cost simply to create ‘anonymized’ copies of data – and this is before any true analytical computing takes place. Immuta solves these problems by enforcing data privacy policies on data at compute-time, dynamically – eliminating the need for additional storage.”, said Steve Touw, Chief Technology Officer, Immuta.

“The proliferation of agile infrastructure, cloud-based machine learning, and the increasing volume of data being moved to the cloud are forcing organizations to take a hard look at cloud-based data access and control. Consistency and compliance will be the key, and Immuta is the only company that can help them ensure long-term success.”, said Rob Lancaster, General Manager, Cloud, Immuta.

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