Search Results: data (5261)

Okera authorizes secure data access for the world’s most demanding companies and regulatory agencies. We help data-driven enterprises of all sizes accelerate innovation, minimize data security risks, and demonstrate regulatory compliance. The Okera Dynamic Access Platform dynamically enforces universal data access control policies to protect confidential, personally identifiable, and regulated data from inappropriate access and misuse. We partner with AWS, Microsoft Azure, and Google, and are a trusted Snowflake Data Access Governance Accelerated partner.

“When I want to think about data as a product, I think about a certain level of accessibility and consumer ability.” – Paige Bartley, 451 Research (part of S&P Global)
Data Mesh is both confusing and compelling, and so is how we think about data – specifically, managing it with users and their desired outcomes in mind.

The goal of a data product is to engender higher utilization of “trusted data” by making its analysis easier by a diverse set of consumers.

Watch this webinar to learn more about how organizations are looking to apply product management practices to their data assets.

It is important for everyone in an organization to use data responsibly. This playbook offers guidance on how to format data to protect confidential, personally identifiable, and regulated data from being inappropriately accessed for various use cases. By de-identifying personal identities from being revealed, you can preserve the privacy of your customers, employees, and partners.

Learn how you can accelerate data safely and securely with dynamic data access policies. This paper will dive into:

What is Data De-Identification?
How to De-Identify PII to Speed Time-to-Insight for your Analysts
De-Identification for Data Analytics
Identify Trends with Partially Tokenized or Masked Data
Format Preserving Tokenization
Non-format Preserving Tokenization
Partial Masking
And more…
Implementing data de-identification with a dynamic policy enforcement solution such as Okera is not hard. By taking a practical approach to data de-identification, you will be more effective and your job will be much easier.