Ketch Partners with Snowflake to Integrate Programmatic Privacy with Comprehensive Data Governance
November 16, 2021 at 09:44 am
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Ketch, announced its partnership with Snowflake and that it has become a Snowflake Accelerated Governance Partner. The partnership and product integrations empower mutual customers to do more with their data, while the designation recognizes Ketch?s innovations in data governance, and its unique approach to programmatic privacy. Companies must comply with rigorous privacy regulations around the storage and use of sensitive and personal data, including new categories of sensitive data defined by laws such as California?s CCPA and CPRA. The integration between Snowflake and Ketch allows joint customers to establish and proactively enforce governance policies that protect and secure the privacy of personal data. With robust data governance policies proactively enforced, data scientists can mobilize data for various analytics and AI initiatives and remain confident that they are in full compliance with regulations and internal company policy. To comply with privacy regulations, an important first step for companies is to understand what types of sensitive and personal data they have, and where that data is stored. Ketch provides ?always-on? data discovery and classification, leveraging Snowflake native features like object tags and labels to inform policy creation and enforcement. An important part of protecting sensitive data is knowing who has access to it, and how data flows across business systems. Ketch allows companies to ask and document: who has accessed data, and how it was used. Snowflake?s Access History capability will inform data lineage reporting in Ketch.
Snowflake Inc. enables every organization to mobilize their data with Snowflakes Data Cloud. The Companyâs platform powers the Data Cloud, enabling customers to consolidate data into a single source of truth to drive meaningful business insights, apply artificial intelligence (AI) to solve business problems, build data applications, and share data and data products. Its platform supports a range of workload, including data warehouse, data lake, data engineering, AI/machine learning (ML), applications, collaboration, cybersecurity, and Unistore. Its cloud-native architecture consists of three independently scalable but logically integrated layers across compute, storage, and cloud services. The compute layer provides dedicated resources to enable users to simultaneously access common data sets for many use cases with minimal latency. The storage layer ingests massive amounts and varieties of structured, semi-structured, and unstructured data to create a unified data record.