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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. Table of Contents. 2) Why Do You Need DQM?

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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 363
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The Lean Analytics Cycle: Metrics > Hypothesis > Experiment > Act

Occam's Razor

To win in business you need to follow this process: Metrics > Hypothesis > Experiment > Act. We are far too enamored with data collection and reporting the standard metrics we love because others love them because someone else said they were nice so many years ago. That metric is tied to a KPI.

Metrics 157
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Monitoring Apache Iceberg metadata layer using AWS Lambda, AWS Glue, and AWS CloudWatch

AWS Big Data

In this blog post, we’ll discuss how the metadata layer of Apache Iceberg can be used to make data lakes more efficient. You will learn about an open-source solution that can collect important metrics from the Iceberg metadata layer. It supports two types of reports: one for commits and one for scans.

Metadata 110
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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 92
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Enhance data governance with enforced metadata rules in Amazon DataZone

AWS Big Data

We’re excited to announce a new feature in Amazon DataZone that offers enhanced metadata governance for your subscription approval process. With this update, domain owners can define and enforce metadata requirements for data consumers when they request access to data assets. Key benefits The feature benefits multiple stakeholders.

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Building Your Human Benchmark with Ontotext Metadata Studio

Ontotext

In text analytics, the human benchmark is a set of documents manually annotated by human experts. 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?