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

AWS Big Data

Prior to the creation of the data lake, Orca’s data was distributed among various data silos, each owned by a different team with its own data pipelines and technology stack. Moreover, running advanced analytics and ML on disparate data sources proved challenging.

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Data Observability and Monitoring with DataOps

DataKitchen

Some will argue that observability is nothing more than testing and monitoring applications using tests, metrics, logs, and other artifacts. That’s a fair point, and it places emphasis on what is most important – what best practices should data teams employ to apply observability to data analytics. Production Analytics.

Testing 214
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Get The Most Out Of Smart Business Intelligence Reporting

datapine

The balance sheet gives an overview of the main metrics which can easily define trends and the way company assets are being managed. Our procurement dashboard above is not only visually balanced but also offers a clear-cut snapshot of every vital metric you need to improve your procurement processes at a glance.

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“You Complete Me,” said Data Lineage to DataOps Observability.

DataKitchen

It allows organizations to see how data is being used, where it is coming from, its quality, and how it is being transformed. DataOps Observability includes monitoring and testing the data pipeline, data quality, data testing, and alerting. Data lineage is static and often lags by weeks or months.

Testing 130
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Introducing Amazon MWAA support for Apache Airflow version 2.7.2 and deferrable operators

AWS Big Data

You can see the time each task spends idling while waiting for the Redshift cluster to be created, snapshotted, and paused. The following graph describes a simple data quality check pipeline using setup and teardown tasks. The Cluster Activity page gathers useful data to monitor your cluster’s live and historical metrics.

Metrics 105
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Take Advantage Of The Top 16 Sales Graphs And Charts To Boost Your Business

datapine

Number 6 on our list is a sales graph example that offers a detailed snapshot of sales conversion rates. A perfect example of how to present sales data, this profit-boosting sales chart offers a panoramic snapshot of your agents’ overall upselling and cross-selling efforts based on revenue and performance. 6) Sales Conversion.

Sales 235