Remove Data Quality Remove Metadata Remove Snapshot Remove Testing
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Amazon DataZone now integrates with AWS Glue Data Quality and external data quality solutions

AWS Big Data

Today, we are pleased to announce that Amazon DataZone is now able to present data quality information for data assets. Other organizations monitor the quality of their data through third-party solutions. Additionally, Amazon DataZone now offers APIs for importing data quality scores from external systems.

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Power enterprise-grade Data Vaults with Amazon Redshift – Part 2

AWS Big Data

Building a starter version of anything can often be straightforward, but building something with enterprise-grade scale, security, resiliency, and performance typically requires knowledge and adherence to battle-tested best practices, and using the right tools and features in the right scenario. system implemented with Amazon Redshift.

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How Amazon Devices scaled and optimized real-time demand and supply forecasts using serverless analytics

AWS Big Data

We also used AWS Lambda for data processing. To further optimize and improve the developer velocity for our data consumers, we added Amazon DynamoDB as a metadata store for different data sources landing in the data lake. Clients access this data store with an API’s.

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How OLX Group migrated to Amazon Redshift RA3 for simpler, faster, and more cost-effective analytics

AWS Big Data

Test environment In order to be confident with the performance of the RA3 nodes, we decided to stress test them in a controlled environment before making the decision to migrate. To do this, we required the following: A reference cluster snapshot – This ensures that we can replay any tests starting from the same state.

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Implement a Multi-Cloud Open Lakehouse with Apache Iceberg in Cloudera Data Platform

Cloudera

With in-place table migration, you can rapidly convert to Iceberg tables since there is no need to regenerate data files. Only metadata will be regenerated. Newly generated metadata will then point to source data files as illustrated in the diagram below. . Data quality using table rollback.

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AWS Glue streaming application to process Amazon MSK data using AWS Glue Schema Registry

AWS Big Data

Therefore, it’s crucial to keep the schema definition in the Schema Registry and the Data Catalog table in sync. To avoid this, it’s recommended to use a data quality check mechanism to identify such anomalies and take appropriate action in case of unexpected behavior. test-schema-registry MSKSchemaName Name of the schema.

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A Summary Of Gartner’s Recent Innovation Insight Into Data Observability

DataKitchen

On 20 July 2023, Gartner released the article “ Innovation Insight: Data Observability Enables Proactive Data Quality ” by Melody Chien. It alerts data and analytics leaders to issues with their data before they multiply. It alerts data and analytics leaders to issues with their data before they multiply.