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6 Expert Tips to enhance Security in Snowflake

As your organization processes petabytes of data in Snowflake, it is vital to protect any personal or sensitive data that might be present.

In this guide, you will learn 6 actions that experts recommend to enhance data security in your Snowflake instance. The top three recommendations are:

  • Discover, Classify, and Catalog all Personal and Sensitive Data in Snowflake
  • Use Snowflake’s Object tagging feature to track sensitive data
  • Mask Sensitive Data dynamically for risk-free data sharing

Download the guide now to discover the three other actions.

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Before protecting personal or sensitive data, organizations must identify and understand the data they have.

It's crucial to learn the best security practices for protecting Snowflake and to have a clear implementation strategy. However, it is up to each individual company to set up and keep up with adequate security measures.

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Our Readers Frequently Ask:

Snowflake secures all incoming data by protecting it with AES-256 strong encryption before saving it in Snowflake tables. Using AES-256 strong encryption, all files kept in internal stages for data loading and unloading are automatically encrypted.

Three distinct layers—Network Security, Identity and Access Management (IAM), and Data Encryption—are used by Snowflake to secure client data. Two-factor authentication, client-side encryption of data import and export, secure data transport and storage, and role-based access control for database objects are all features that Snowflake implements.

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At Securiti, our mission is to enable enterprises to safely harness the incredible power of data and the cloud by controlling the complex security, privacy and compliance risks.

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