Remove 2020 Remove Blog Remove Data Governance Remove Data Silos
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Snowcase Study: How Data Governance Gives Texas Mutual Insurance Company a Competitive Edge

Alation

Much of his work focuses on democratising data and breaking down data silos to drive better business outcomes. In this blog, Chris shows how Snowflake and Alation together accelerate data culture. He shows how Texas Mutual Insurance Company has embraced data governance to build trust in data.

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Why Your Data Governance Strategy is Failing

Alation

What is data governance and how do you measure success? Data governance is a system for answering core questions about data. It begins with establishing key parameters: What is data, who can use it, how can they use it, and why? Why is your data governance strategy failing?

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Common Data Governance Challenges & Their Solutions

Alation

Common Data Governance Challenges. Every enterprise runs into data governance challenges eventually. Issues like data visibility, quality, and security are common and complex. Data governance is often introduced as a potential solution. And one enterprise alone can generate a world of data.

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What is the Snowflake Data Cloud and How Much Does it Cost?

phData

This blog was originally written by Keith Smith and updated for 2024 by Justin Delisi. Snowflake’s Data Cloud has emerged as a leader in cloud data warehousing. What is the Snowflake Data Cloud? What Components Make up the Snowflake Data Cloud?

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Enterprise Analytics: Key Challenges & Strategies

Alation

In enterprises especially, which typically collect vast amounts of data, analysts often struggle to find, understand, and trust data for analytics reporting. Immense volume leads to data silos, and a holistic view of the business becomes more difficult to achieve. Implementing adaptive, active data governance.

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Federated Learning on AWS with FedML: Health analytics without sharing sensitive data – Part 1

AWS Machine Learning Blog

This blog post is co-written with Chaoyang He and Salman Avestimehr from FedML. In recent years, this new learning paradigm has been successfully adopted to address the concern of data governance in training ML models. This allows you to train an ML model on distributed data, without the need to share or move it.

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Federated Learning on AWS with FedML: Health analytics without sharing sensitive data – Part 2

AWS Machine Learning Blog

This blog post is co-written with Chaoyang He and Salman Avestimehr from FedML. We set up a multi-account architecture, where in a real-world scenario, hospitals or healthcare organizations can join the ecosystem to benefit from collaborative learning while maintaining data governance. 2020): e0235424. Plos one 15.7

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