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Snowflake’s Data Classification Lets You Identify and Tag Sensitive Data Directly in Snowsight

Snowflake

We recognize the critical importance of quickly identifying and safeguarding sensitive data objects, and we consistently strive to provide solutions that help achieve these goals — from advancements such as classification and tag-based policies to the intuitive Data Governance UI. Ready to try Data Classification for yourself?

Data 96
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Data News — Week 24.02

Christophe Blefari

dbt meta tag — A list of the companies habing product features depending on the meta tag. Unit testing dbt models — Using a dbt-unit-testing package Matthieu showcases how you can easily test your models. It shows how deeply dbt change the data world.

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Complying with Quebec’s Data Privacy Laws Is Easier with the Data Cloud

Snowflake

Among the many reasons Snowflake is integral to an organization’s data strategy is the out-of-the-box security-related features. In today’s rapidly changing regulatory and compliance landscape, use of these features allows customers to keep critical data secure and monitor that data for auditing purposes. Division I.1

Cloud 75
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A New Horizon for Data Reliability With Monte Carlo and Snowflake

Monte Carlo

Monte Carlo is thrilled to be part of the Snowflake Horizon partner ecosystem as we leverage many of the pre-built features Snowflake provides in order to help organizations reduce their data downtime and improve data quality at scale. Did one of the 58 dashboards tagged for marketing stop loading fresh data? Route it to fix ASAP.

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How to Package and Price Embedded Analytics

Just by embedding analytics, application owners can charge 24% more for their product. How much value could you add? This framework explains how application enhancements can extend your product offerings. Brought to you by Logi Analytics.

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Type-safe data processing pipelines

Tweag

Consider your favorite compiler: it consists of a lexical and syntactical analyzer, a possible preprocessor, some optimization passes (which can be turned on or off), various optional static analysis features, a code generator, and so on. Even then, however, GHC will not complain if we write myPipeline = monomorphize.

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Machine Learning for Fraud Detection in Streaming Services

Netflix Tech

Even though such techniques can scale security solutions proportional to the service size, they bring their own set of challenges such as requiring labeled data samples, defining effective features, and finding appropriate algorithms. Based on this reasoning, we tag all the accounts that acquire licenses very quickly as anomalous.