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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

1) What Is Data Quality Management? 4) Data Quality Best Practices. 5) How Do You Measure Data Quality? 6) Data Quality Metrics Examples. 7) Data Quality Control: Use Case. 8) The Consequences Of Bad Data Quality. 9) 3 Sources Of Low-Quality Data. 10) Data Quality Solutions: Key Attributes.

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Mastering Data Analysis Report and Dashboard

FineReport

In the realm of big data utilization , we often romanticize its profound impact, envisioning scenarios like precision-targeted advertising, streamlined social security management, and the intelligent evolution of the pharmaceutical sector. Try FineReport Now 1. Try FineReport Now 1.1 Try FineReport Now 1.1

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BMW Cloud Efficiency Analytics powered by Amazon QuickSight and Amazon Athena

AWS Big Data

The CLEA dashboards were built on the foundation of the Well-Architected Lab. For more information on this foundation, refer to A Detailed Overview of the Cost Intelligence Dashboard. The difference lies in when and where data transformation takes place. These ingested datasets are used as a source in CLEA dashboards.

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Modernize a legacy real-time analytics application with Amazon Managed Service for Apache Flink

AWS Big Data

In this post, we discuss ways to modernize your legacy, on-premises, real-time analytics architecture to build serverless data analytics solutions on AWS using Amazon Managed Service for Apache Flink. Near-real-time streaming analytics captures the value of operational data and metrics to provide new insights to create business opportunities.

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Deep dive into the AWS ProServe Hadoop Migration Delivery Kit TCO tool

AWS Big Data

Amazon QuickSight dashboards showcase the results from the analyzer. With QuickSight, you can visualize YARN log data and conduct analysis against the datasets generated by pre-built dashboard templates and a widget. This step creates datasets on QuickSight dashboards in your AWS target account.

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How Chime Financial uses AWS to build a serverless stream analytics platform and defeat fraudsters

AWS Big Data

To make high-quality decisions, we need to collect user event data from various sources and update risk profiles in real time. We also need to be able to add new fields and metrics to the risk profiles as our team identifies new attacks, without needing engineering intervention or complex deployments.

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Connect your data for faster decisions with AWS

AWS Big Data

Second, organizations still need transformations like cleansing, deduplication, and combining datasets for analysis and machine learning (ML). For these, AWS Glue provides fast, scalable data transformation. They can now analyze business metrics in near-real time and make data-driven decisions faster than ever before.