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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

5) How Do You Measure Data Quality? 6) Data Quality Metrics Examples. In this article, we will detail everything which is at stake when we talk about DQM: why it is essential, how to measure data quality, the pillars of good quality management, and some data quality control techniques. How Do You Measure Data Quality?

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Deploy Amazon QuickSight dashboards to monitor AWS Glue ETL job metrics and set alarms

AWS Big Data

In this post, we explore how to combine AWS Glue usage information and metrics with centralized reporting and visualization using QuickSight. You have metrics available per job run within the AWS Glue console, but they don’t cover all available AWS Glue job metrics, and the visuals aren’t as interactive compared to the QuickSight dashboard.

Metrics 90
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Building Your Human Benchmark with Ontotext Metadata Studio

Ontotext

You’ll also be able to establish an inter-annotator agreement (IAA) metric. This measures the consistency of annotations when more than one person is involved in the process. What Are The Benefits Of Using Ontotext Metadata Studio? Ontotext Metadata Studio addresses all of these problems head on.

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Disaster recovery strategies for Amazon MWAA – Part 1

AWS Big Data

Within Airflow, the metadata database is a core component storing configuration variables, roles, permissions, and DAG run histories. A healthy metadata database is therefore critical for your Airflow environment. The third component is for creating and storing backups of all configurations and metadata that is required to restore.

Strategy 102
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Modernize a legacy real-time analytics application with Amazon Managed Service for Apache Flink

AWS Big Data

Near-real-time streaming analytics captures the value of operational data and metrics to provide new insights to create business opportunities. These metrics help agents improve their call handle time and also reallocate agents across organizations to handle pending calls in the queue.

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The Future of Data Lineage and the Role of Metadata

Alation

It’s important to realize that we need visibility into lineage and relationships between all data and data-related assets, including business terms, metric definitions, policies, quality rules, access controls, algorithms, etc. Active metadata will play a critical role in automating such updates as they arise. Why Focus on Lineage?

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Bringing an AI Product to Market

O'Reilly on Data

The first step in building an AI solution is identifying the problem you want to solve, which includes defining the metrics that will demonstrate whether you’ve succeeded. It sounds simplistic to state that AI product managers should develop and ship products that improve metrics the business cares about. Agreeing on metrics.

Marketing 361