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How Retail and Media Leaders Drive Customer Satisfaction and Profits with Data and AI

Snowflake

Attendees will discover how to accelerate their critical business workflows with the right data, technology and ecosystem access. Explore AI and unstructured data processing use cases with proven ROI: This year, retailers and brands will face intense pressure to demonstrate tangible returns on their AI investments.

Retail 96
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Mastering Multi-Cloud with Cloudera: Strategic Data & AI Deployments Across Clouds

Cloudera

A leading meal kit provider migrated its data architecture to Cloudera on AWS, utilizing Cloudera’s Open Data Lakehouse capabilities. This transition streamlined data analytics workflows to accommodate significant growth in data volumes.

Cloud 82
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Unstructured Data: Examples, Tools, Techniques, and Best Practices

AltexSoft

In today’s data-driven world, organizations amass vast amounts of information that can unlock significant insights and inform decision-making. A staggering 80 percent of this digital treasure trove is unstructured data, which lacks a pre-defined format or organization. What is unstructured data?

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2024 Governance Trends for Data Leaders

phData: Data Engineering

Strong data governance also lays the foundation for better model performance, cost efficiency, and improved data quality, which directly contributes to regulatory compliance and more secure AI systems. However, implementation in a large complex environment is difficult due to investment challenges and buy-in from the business.

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Chose Both: Data Fabric and Data Lakehouse

Cloudera

And second, for the data that is used, 80% is semi- or unstructured. Combining and analyzing both structured and unstructured data is a whole new challenge to come to grips with, let alone doing so across different infrastructures. Consistent data security and governance across all fabrics. Better together.

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How Cloudera Data Flow Enables Successful Data Mesh Architectures

Cloudera

Those decentralization efforts appeared under different monikers through time, e.g., data marts versus data warehousing implementations (a popular architectural debate in the era of structured data) then enterprise-wide data lakes versus smaller, typically BU-Specific, “data ponds”.

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Data Engineering: A Formula 1-inspired Guide for Beginners

Towards Data Science

Anyways, I wasn’t paying enough attention during university classes, and today I’ll walk you through data layers using —  guess what  —  an example. Business Scenario & Data Architecture Imagine this: next year, a new team on the grid, Red Thunder Racing, will call us (yes, me and you) to set up their new data infrastructure.