Remove tag automation
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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 99
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Just Launched: Data Products

Monte Carlo

Users simply select the dashboard or table that matters to them and Monte Carlo automatically tags and groups everything that is upstream of those assets that are connected via Lineage. You can also add in non-lineage-connected assets that you consider part of your Data Product definition if you choose. Speak to our team.

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How DoorDash Migrated from StatsD to Prometheus

DoorDash Engineering

Challenges Faced With StatsD StatsD was a great asset for our early observability needs, but we began encountering constraints such as losing metrics during surge events, difficulties with naming/standardized tags, and a lack of reporting tools. We’ll briefly introduce StatD’s history before diving into those specific issues.

AWS 82
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A New Horizon for Data Reliability With Monte Carlo and Snowflake

Monte Carlo

Improve coverage with automated anomaly detection Monte Carlo uses machine learning detectors to monitor the health of data pipelines across dimensions like: Data freshness : Did the data arrive when we expected? Did one of the 58 dashboards tagged for marketing stop loading fresh data? Did an alert pop up for a critical Gold table?

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Cloud Analytics Powered by FinOps

Cloudera

Resource tagging CDP Public Cloud allows administrators to easily add tags to the Data Service and resources the platform deploys on the company’s cloud tenant. Afterward, those tags are also used to track resource usage, assign usage to cost centers/departments, and trigger automation policies.

Cloud 77
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Introducing Vector Search on Rockset: How to run semantic search with OpenAI and Rockset

Rockset

Before vector search, search experiences primarily relied on keyword search, which frequently involved manually tagging data to identify and deliver relevant results. As an example, if we wanted to search for tagged keywords to deliver product results, we would need to manually tag “Fortnite” as a ”survival game” and ”multiplayer game.”

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Machine Learning for Fraud Detection in Streaming Services

Netflix Tech

On the other hand, in model-based anomaly detection approaches, models are built and used to detect anomalous incidents in a fairly automated manner. Based on this reasoning, we tag all the accounts that acquire licenses very quickly as anomalous. false-positive incidents), for example in the case of a buggy client or device.