Remove Data Processing Remove Metadata Remove Metrics
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The Ultimate Guide to Modern Data Quality Management (DQM) For An Effective Data Quality Control Driven by The Right Metrics

datapine

6) Data Quality Metrics Examples. Reporting being part of an effective DQM, we will also go through some data quality metrics examples you can use to assess your efforts in the matter. It involves: Reviewing data in detail Comparing and contrasting the data to its own metadata Running statistical models Data quality reports.

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Use Amazon Kinesis Data Streams to deliver real-time data to Amazon OpenSearch Service domains with Amazon OpenSearch Ingestion

AWS Big Data

For example, you can use metadata about the Kinesis data stream name to index by data stream ( ${getMetadata("kinesis_stream_name") ), or you can use document fields to index data depending on the CloudWatch log group or other document data ( ${path/to/field/in/document} ).

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Accelerate your migration to Amazon OpenSearch Service with Reindexing-from-Snapshot

AWS Big Data

Each Lucene index (and, therefore, each OpenSearch shard) represents a completely independent search and storage capability hosted on a single machine. How RFS works OpenSearch and Elasticsearch snapshots are a directory tree that contains both data and metadata. The following is an example for the structure of an Elasticsearch 7.10

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How REA Group approaches Amazon MSK cluster capacity planning

AWS Big Data

In each environment, Hydro manages a single MSK cluster that hosts multiple tenants with differing workload requirements. Solution overview The MSK clusters in Hydro are configured with a PER_TOPIC_PER_BROKER level of monitoring, which provides metrics at the broker and topic levels.

Metrics 97
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How EUROGATE established a data mesh architecture using Amazon DataZone

AWS Big Data

From here, the metadata is published to Amazon DataZone by using AWS Glue Data Catalog. The applications are hosted in dedicated AWS accounts and require a BI dashboard and reporting services based on Tableau. This process is shown in the following figure.

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Enhance monitoring and debugging for AWS Glue jobs using new job observability metrics, Part 3: Visualization and trend analysis using Amazon QuickSight

AWS Big Data

In Part 2 of this series, we discussed how to enable AWS Glue job observability metrics and integrate them with Grafana for real-time monitoring. In this post, we explore how to connect QuickSight to Amazon CloudWatch metrics and build graphs to uncover trends in AWS Glue job observability 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.