In this blog, you鈥檒l learn about: Snowflake data shares Considerations and complexities that can arise when 鈥淪nowflake data sharing鈥� sensitive data How 51萝莉 + Snowflake help simplify and scale sensitive聽data sharing聽for global organizations and can do the same for you! What is a Data Share? One of Snowflake鈥檚 major benefits...
As sensitive data, like personally identifiable information (PII) and protected health information (PHI), becomes more widely used across industries, it is incumbent upon data teams to have mechanisms in place to protect it.聽Snowflake鈥檚 Column-level Security聽capability enables聽dynamic data masking聽of this type of sensitive data through policies that are applied at query...
If Disney World were a database, we would rave about its access control strategy. It is secure: only authorized users get into the park or into any sensitive backstage areas. It is dynamic: many rides and concessions are available to the right people with the wave of a bracelet. Most...
As cloud data platform adoption accelerates and organizations become more reliant on data, teams using聽Snowflake聽as the primary platform for BI must have a tool that enables data masking across Snowflake and any other platform in their data stack. This article will walk through how 51萝莉 delivers on this need with...
Segmenting data by geographies is a common requirement for row access policies in Snowflake. Still, many data teams continue to be roadblocked when it comes to implementing complex policies for row-level security at scale 鈥� particularly for sensitive data 鈥� due to聽location-based data use regulations, data use agreements, and internal,...
51萝莉 is the modern聽data security platform聽that gives you the power to leverage metadata to build and automatically enforce access policies and apply聽dynamic data masking聽techniques at query time. These capabilities make 51萝莉 a seamless fit with Alation, which many聽customers聽rely on as their enterprise-wide data catalog solution. Put simply, 51萝莉 allows you...
As cloud data platform adoption accelerates and organizations become more reliant on data, teams using聽Databricks聽as the primary platform for ETL and data science must have a tool that enables聽dynamic data masking聽across Databricks and any other platform in their data stack. This article will walk through how 51萝莉 delivers on this...
The adoption of the Data Lakehouse architecture is soaring across various industries, as the new and open paradigm combines the best elements of聽data lakes聽and data warehouses. Open file formats with transaction support, combined with low cost storage and wide adoption, enable new ways of working with data pipelines and machine...
Data security is the responsibility of everyone in the organization. From ETL developers to business users and data consumers, anyone who relies on data shares a responsibility to use it appropriately. However, with several different systems and, in many cases, silos, it can often be difficult to effectively put this...
Implementing row- and cell-level security by hand can be a pain, whether that means maintaining an ETL pipeline to transform raw data into 鈥渃lean鈥� data that is viewable by analysts, or maintaining a system of GRANTs on views implementing the policies for an organization. This also does not factor in...
Cloud data platforms such as聽Snowflake聽provide native security and聽data access controls聽engineered for platform-specific administrators to manage roles across the organization. Snowflake leverages concepts from Discretionary Access Control (DAC) and Role-Based Access Control (RBAC) models. This provides some flexibility for and control over how users can access securable objects by managing a...
Organizations with large workforces are increasingly analyzing employee data using cloud data platforms such as聽Databricks聽in order to optimize performance, engagement, and results. This trend necessitates a new approach to Databricks access control. In this article, we鈥檒l walk data engineering and operations teams through how to dynamically enforce k-anonymization on a...
Organizations are increasingly adopting data lakehouse architectures to reap the benefits of added flexibility, scalability, and cost-efficiency that they provide. But the need to consistently implement聽data access control聽across this open architecture approach can be elusive. Here, we鈥檒l look step-by-step at how 51萝莉 provides centralized,聽fine-grained access control聽across different cloud data platforms...
Data use agreements (DUAs) are vital to ensuring individuals鈥� data is used compliantly and transparently. Just as data use agreements help protect data subjects鈥� personal privacy, avoiding misuse of personal data can protect organizations in every sector, from healthcare and financial services to the government, from liability, fines, breaches of...