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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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Build event-driven data pipelines using AWS Controllers for Kubernetes and Amazon EMR on EKS

AWS Big Data

An event-driven architecture is a software design pattern in which decoupled applications can asynchronously publish and subscribe to events via an event broker. Amazon Elastic Kubernetes Service (Amazon EKS) is becoming a popular choice among AWS customers to host long-running analytics and AI or machine learning (ML) workloads.

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Petabyte-scale log analytics with Amazon S3, Amazon OpenSearch Service, and Amazon OpenSearch Ingestion

AWS Big Data

Organizations often need to manage a high volume of data that is growing at an extraordinary rate. At the same time, they need to optimize operational costs to unlock the value of this data for timely insights and do so with a consistent performance. We think of this concept as inside-out data movement. Example Corp.

Data Lake 117
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Modernize your ETL platform with AWS Glue Studio: A case study from BMS

AWS Big Data

In addition to using native managed AWS services that BMS didn’t need to worry about upgrading, BMS was looking to offer an ETL service to non-technical business users that could visually compose data transformation workflows and seamlessly run them on the AWS Glue Apache Spark-based serverless data integration engine.

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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

QuickSight makes it straightforward for business users to visualize data in interactive dashboards and reports. You can slice data by different dimensions like job name, see anomalies, and share reports securely across your organization. With these insights, teams have the visibility to make data integration pipelines more efficient.

Metrics 109
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How Data Governance Protects Sensitive Data

erwin

Organizations are managing more data than ever. With more companies increasingly migrating their data to the cloud to ensure availability and scalability, the risks associated with data management and protection also are growing. Data Security Starts with Data Governance. Who is authorized to use it and how?

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KGF 2023: Bikes To The Moon, Datastrophies, Abstract Art And A Knowledge Graph Forum To Embrace Them All

Ontotext

It enriched their understanding of the full spectrum of knowledge graph business applications and the technology partner ecosystem needed to turn data into a competitive advantage. Content and data management solutions based on knowledge graphs are becoming increasingly important across enterprises.