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Data Integrity for AI: What’s Old is New Again

Precisely

Does the LLM capture all the relevant data and context required for it to deliver useful insights? Not to mention the crazy stories about Gen AI making up answers without the data to back it up!) Are we allowed to use all the data, or are there copyright or privacy concerns? But simply moving the data wasnt enough.

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Setting up Data Lake on GCP using Cloud Storage and BigQuery

Analytics Vidhya

Introduction A data lake is a centralized and scalable repository storing structured and unstructured data. The need for a data lake arises from the growing volume, variety, and velocity of data companies need to manage and analyze.

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Snowflake PARSE_DOC Meets Snowpark Power

Cloudyard

Read Time: 2 Minute, 33 Second Snowflakes PARSE_DOCUMENT function revolutionizes how unstructured data, such as PDF files, is processed within the Snowflake ecosystem. Traditionally, this function is used within SQL to extract structured content from documents. Apply advanced data cleansing and transformation logic using Python.

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Accelerate AI Development with Snowflake

Snowflake

At Snowflake BUILD , we are introducing powerful new features designed to accelerate building and deploying generative AI applications on enterprise data, while helping you ensure trust and safety. These scalable models can handle millions of records, enabling you to efficiently build high-performing NLP data pipelines.

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8 Essential Data Pipeline Design Patterns You Should Know

Monte Carlo

Let’s set the scene: your company collects data, and you need to do something useful with it. Whether it’s customer transactions, IoT sensor readings, or just an endless stream of social media hot takes, you need a reliable way to get that data from point A to point B while doing something clever with it along the way.

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Microsoft Fabric Architecture Explained: Core Components & Benefit

Edureka

Microsoft Fabric is a next-generation data platform that combines business intelligence, data warehousing, real-time analytics, and data engineering into a single integrated SaaS framework. The architecture of Microsoft Fabric is based on several essential elements that work together to simplify data processes: 1.

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Data Vault on Snowflake: Feature Engineering and Business Vault

Snowflake

A 2016 data science report from data enrichment platform CrowdFlower found that data scientists spend around 80% of their time in data preparation (collecting, cleaning, and organizing of data) before they can even begin to build machine learning (ML) models to deliver business value.