Best Data Masking Software for Google Cloud BigQuery

Satori is a Data Security Platform (DSP) that enables self-service data and analytics for data-driven companies. With Satori, users have a personal data portal where they can see all available datasets and gain immediate access to them. That means your data consumers get data access in seconds instead of weeks. Satori’s DSP dynamically applies the appropriate security and access policies, reducing manual data engineering work. Satori’s DSP manages access, permissions, security, and compliance policies - all from a single console. Satori continuously classifies sensitive data in all your data stores (databases, data lakes, and data warehouses), and dynamically tracks data usage while applying relevant security policies. Satori enables your data use to scale across the company while meeting all data security and compliance requirements.

Immuta's Data Access Platform is built to give data teams secure yet streamlined access to data. Every organization is grappling with complex data policies as rules and regulations around that data are ever-changing and increasing in number. Immuta empowers data teams by automating the discovery and classification of new and existing data to speed time to value; orchestrating the enforcement of data policies through Policy-as-code (PaC), data masking, and Privacy Enhancing Technologies (PETs) so that any technical or business owner can manage and keep it secure; and monitoring/auditing user and policy activity/history and how data is accessed through automation to ensure provable compliance. Immuta integrates with all of the leading cloud data platforms, including Snowflake, Databricks, Starburst, Trino, Amazon Redshift, Google BigQuery, and Azure Synapse. Our platform is able to transparently secure data access without impacting performance. With Immuta, data teams are able to speed up data access by 100x, decrease the number of policies required by 75x, and achieve provable compliance goals.

Our platform allows businesses to use data, including its application in advanced analysis, machine learning and AI, to do great things without worrying that customers, employees or intellectual property are at risk. The Protegrity Data Protection Platform does more than just protect data. It also classifies and discovers data, while protecting it. It is impossible to protect data you don't already know about. Our platform first categorizes data, allowing users the ability to classify the type of data that is most commonly in the public domain. Once those classifications are established, the platform uses machine learning algorithms to find that type of data. The platform uses classification and discovery to find the data that must be protected. The platform protects data behind many operational systems that are essential to business operations. It also provides privacy options such as tokenizing, encryption, and privacy methods.

Multi-cloud data security with a single pane of glass Industry's first SaaS access governance solution. Cloud is fragmented and data is scattered across different systems. Sensitive data is difficult to access and control due to limited visibility. Complex data onboarding hinders data scientist productivity. Data governance across services can be manual and fragmented. It can be time-consuming to securely move data to the cloud. Maximize visibility and assess the risk of sensitive data distributed across multiple cloud service providers. One system that enables you to manage multiple cloud services' data policies in a single place. Support RTBF, GDPR and other compliance requests across multiple cloud service providers. Securely move data to the cloud and enable Apache Ranger compliance policies. It is easier and quicker to transform sensitive data across multiple cloud databases and analytical platforms using one integrated system.

You have the freedom to choose the anonymization method that best suits your needs - including tokenization, encryption, and masking techniques. This will ensure that sensitive data is protected in a delicate balance between security and performance. You can choose from over 60 different anonymization methods to protect sensitive data. Anonymization methods that provide consistent results across datastores and applications will help you maintain referential integrity. Anonymization methods that provide both performance and protection. You can choose to encrypt, tokenize or mask data depending on the use case. There are many ways to anonymize sensitive data. Each method provides adequate security and data usability. Protect sensitive data across data storage and applications, and maintain referential integrity. You can choose from a range of NIST-approved encryption or tokenization algorithms.

iMask protects sensitive data at the Application Layer as well as the Database Layer. It offers flexible solutions that can be used for all types of use and all users, small, medium and large. Mask sensitive data at both the application and database levels to ensure your data's protection in production. You can set up rules in the product UI to allow role-based and user-based access controls that control who can access your sensitive information. You have the option to choose from more than 40 anonymization methods to maintain data consistency between production and nonproduction instances. You can set authorization rules to restrict who can see sensitive data based on geography, roles, departments, and other factors. Secure anonymization protocols can be enabled without affecting performance. Database embedded approach allows data to be deidentified without any changes in the application architecture or security protocols.