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Run Apache XTable in AWS Lambda for background conversion of open table formats

AWS Big Data

This post was co-written with Dipankar Mazumdar, Staff Data Engineering Advocate with AWS Partner OneHouse. Data architecture has evolved significantly to handle growing data volumes and diverse workloads. In Amazon S3 and AWS Glue, we can see our Hudi dataset and table along with the metadata folder.hoodie.

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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.

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Apache Ozone – A Multi-Protocol Aware Storage System

Cloudera

Are you struggling to manage the ever-increasing volume and variety of data in today’s constantly evolving landscape of modern data architectures? Hive, Spark, Impala, YARN, BI tools with S3 connectors can interact with Ozone using the s3a protocol. Only expected to be used by cluster administrators.

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SAP enhances Datasphere and SAC for AI-driven transformation

CIO Business Intelligence

Vector embeddings represent data (including unstructured data like text, images, and videos) as coordinates while capturing their semantic relationships and similarities. The SAP HANA Cloud Vector Engine, unveiled a few months ago , is a multi-model engine that can store and query vector embeddings like any other data type.

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The Future Is Hybrid Data, Embrace It

Cloudera

In the past decade, the amount of structured data created, captured, copied, and consumed globally has grown from less than 1 ZB in 2011 to nearly 14 ZB in 2020. Impressive, but dwarfed by the amount of unstructured data, cloud data, and machine data – another 50 ZB. Fuel growth with speed and control.

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Data democratization: How data architecture can drive business decisions and AI initiatives

IBM Big Data Hub

Traditionally, data was seen as information to be put on reserve, only called upon during customer interactions or executing a program. Today, the way businesses use data is much more fluid; data literate employees use data across hundreds of apps, analyze data for better decision-making, and access data from numerous locations.

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Accelerating generative AI requires the right storage

CIO Business Intelligence

Unstructured data needs for generative AI Generative AI architecture and storage solutions are a textbook case of “what got you here won’t get you there.” In addition, managing the data created by generative AI models is becoming a crucial aspect of the AI lifecycle.