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

Precisely

The goal of this post is to understand how data integrity best practices have been embraced time and time again, no matter the technology underpinning. In the beginning, there was a data warehouse The data warehouse (DW) was an approach to data architecture and structured data management that really hit its stride in the early 1990s.

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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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The Rise of Unstructured Data

Cloudera

Seagate Technology forecasts that enterprise data will double from approximately 1 to 2 Petabytes (one Petabyte is 10^15 bytes) between 2020 and 2022. The amount of data created over the next 3 years is expected to be more than the data created over the past 30 years. Here we mostly focus on structured vs unstructured data.

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Your Enterprise Data Needs an Agent

Snowflake

Agents need to access an organization's ever-growing structured and unstructured data to be effective and reliable. As data connections expand, managing access controls and efficiently retrieving accurate informationwhile maintaining strict privacy protocolsbecomes increasingly complex.

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Bring Order To The Chaos Of Your Unstructured Data Assets With Unstruk

Data Engineering Podcast

Summary Working with unstructured data has typically been a motivation for a data lake. Kirk Marple has spent years working with data systems and the media industry, which inspired him to build a platform for automatically organizing your unstructured assets to make them more valuable.

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Simplifying Multimodal Data Analysis with Snowflake Cortex AI

Snowflake

This major enhancement brings the power to analyze images and other unstructured data directly into Snowflakes query engine, using familiar SQL at scale. Unify your structured and unstructured data more efficiently and with less complexity. Introducing Cortex AI COMPLETE Multimodal , now in public preview.

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What is an AI Data Engineer? 4 Important Skills, Responsibilities, & Tools

Monte Carlo

Key Differences Between AI Data Engineers and Traditional Data Engineers While traditional data engineers and AI data engineers have similar responsibilities, they ultimately differ in where they focus their efforts. Challenges Faced by AI Data Engineers Just because “AI” involved doesn’t mean all the challenges go away!