Tag: Snowflake

Cortex Parse Document Guide & Best Practices

The purpose of this article is to provide a step-by-step guide and best practices for Snowflake Cortex’s Parse Document functionality. If you’re interested in an overview of this

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Introduction to Snowflake Cortex Parse Document

In a previous article, we touched on Snowflake’s managed AI/ML offering, Cortex. The purpose of this article is to provide a high-level overview a specific functionality, parsing documents

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SOX Compliance in the Modern Data Stack

Overview  The purpose of this article is to showcase how SOX compliance audits make their way to the modern data stack. Specifically, how we helped one of our

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Snowflake Connector for Python 

Overview This blog will help you to understand the latest cloud data warehousing platform called snowflake, connection with python.   As a python developer I always wanted to do

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How to Build RBAC in Snowflake

This blog is intended to provide a baseline knowledge of Role Based Access Control (RBAC) is and the different types of roles available in Snowflake. As a Select

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Enhance Customer Contact Touchpoint Analysis 

Overview As a trusted data advisor for a major insurance company, the CloudEQS team delivered a project to better analyze data from their call center.   This case study

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Introduction to Snowflake Cortex 

Overview   The purpose of this article is to provide a high-level overview of Snowflake’s AI/ML offerings – Snowflake Cortex. This is intended to provide a consolidated overview

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Reducing Call Center Operational Costs 

Overview of the Project  In a rapidly evolving insurance landscape, we partnered with a leading insurance provider to tackle a critical business challenge: high operational costs associated with

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Data Pipeline Observability, A Streamlit Application

Overview   One of our recent client projects struggled with observing their data pipelines across their two vendors – Matillion & DBT. This article addresses how the CloudEQS team

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Optimizing Data Platform Foundations For AI

Overview of the Project  Just because an organization has a “Modern Data Stack” doesn’t mean all their problems are solved.   Additionally, organizations can’t accelerate the adoption of GenAI

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