Remove Data Processing Remove Experimentation Remove Metadata Remove Metrics
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What you need to know about product management for AI

O'Reilly on Data

But there’s a host of new challenges when it comes to managing AI projects: more unknowns, non-deterministic outcomes, new infrastructures, new processes and new tools. You might have millions of short videos , with user ratings and limited metadata about the creators or content.

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Orca Security’s journey to a petabyte-scale data lake with Apache Iceberg and AWS Analytics

AWS Big Data

This data is sent to Apache Kafka, which is hosted on Amazon Managed Streaming for Apache Kafka (Amazon MSK). Additionally, partition evolution enables experimentation with various partitioning strategies to optimize cost and performance without requiring a rewrite of the table’s data every time.

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Introducing the vector engine for Amazon OpenSearch Serverless, now in preview

AWS Big Data

This enables you to process a user’s query to find the closest vectors and combine them with additional metadata without relying on external data sources or additional application code to integrate the results. You can choose to host your collection on a public endpoint or within a VPC. The vector index supports up to 1,000 fields.

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Amazon OpenSearch Service search enhancements: 2023 roundup

AWS Big Data

Now users seek methods that allow them to get even more relevant results through semantic understanding or even search through image visual similarities instead of textual search of metadata. It similarly codes the query as a vector and then uses a distance metric to find nearby vectors in the multi-dimensional space to find matches.

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What’s new with Amazon MWAA support for Apache Airflow version 2.4.3

AWS Big Data

If your updates to a dataset triggers multiple subsequent DAGs, then you can use the Airflow metric max_active_tasks_per_dag to control the parallelism of the consumer DAG and reduce the chance of overloading the system. The workflow steps are as follows: The producer DAG makes an API call to a publicly hosted API to retrieve data.

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Improving Multi-tenancy with Virtual Private Clusters

Cloudera

The typical Cloudera Enterprise Data Hub Cluster starts with a few dozen nodes in the customer’s datacenter hosting a variety of distributed services. While this approach provides isolation, it creates another significant challenge: duplication of data, metadata, and security policies, or ‘split-brain’ data lake. Cloudera Manager 6.2