article thumbnail

Getting started with Kafka client metrics

IBM Big Data Hub

One key advantage of opting for managed Kafka services is the delegation of responsibility for broker and operational metrics, allowing users to focus solely on metrics specific to applications. With Kafka, monitoring typically involves various metrics that are related to topics, partitions, brokers and consumer groups.

Metrics 99
article thumbnail

The Ultimate Guide to Modern Data Quality Management (DQM) For An Effective Data Quality Control Driven by The Right Metrics

datapine

6) Data Quality Metrics Examples. Reporting being part of an effective DQM, we will also go through some data quality metrics examples you can use to assess your efforts in the matter. The data quality analysis metrics of complete and accurate data are imperative to this step. Table of Contents. 2) Why Do You Need DQM?

Insiders

Sign Up for our Newsletter

This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.

article thumbnail

The hard truth of IT metrics

CIO Business Intelligence

And if you think you need metrics to manage you might be feeling guilty about not having enough of them. Good metrics are hard to craft, harder to manage, expensive to maintain, and perishable besides. Bad metrics, in contrast, are easier all the way around, but that doesn’t matter. Bad metrics are worse than no metrics.

Metrics 105
article thumbnail

DataKitchen Resource Guide To Data Journeys & Data Observability & DataOps

DataKitchen

Webinar: Beyond Data Observability: Personalization DataKitchen DataOps Observability Problem Statement White Paper: ‘Taming Chaos’ Technical Product Overview Four-minute online demo Detailed Product: Documentation Webinar: Data Observability Demo Day DataKitchen DataOps TestGen Problem Statement White Paper: ‘Mystery Box Full Of Data Errors’ (..)

Testing 120
article thumbnail

KDnuggets™ News 19:n39, Oct 16: Key Ideas in Document Embedding; The problem with metrics is a big problem for AI

KDnuggets

This week on KDnuggets: Beyond Word Embedding: Key Ideas in Document Embedding; The problem with metrics is a big problem for AI; Activation maps for deep learning models in a few lines of code; There is No Such Thing as a Free Lunch; 8 Paths to Getting a Machine Learning Job Interview; and much, much more.

Metrics 50
article thumbnail

Preliminary Thoughts on the White House Executive Order on AI

O'Reilly on Data

The recent discovery (documented by an exposé in The Atlantic ) that OpenAI, Meta, and others used databases of pirated books, for example, highlights the need for transparency in training data. Operational Metrics.

article thumbnail

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 156