CIO Business Intelligence

MAY 16, 2022

In 2011, another update — dubbed ITIL 2011 — was published under the Cabinet Office. ITIL 4 contains seven guiding principles that were adopted from the most recent ITIL Practitioner Exam, which covers organizational change management, communication, and measurement and metrics. How does ITIL reduce costs?

IT 105

IT Cost-Benefit ROI Risk 105

Occam's Razor

APRIL 25, 2011

Making lame metrics the measures of success: Impressions, Click-throughs, Page Views. Use metrics that matter: Loyalty, Recency , Net Profit, Conversation Rate, Message Amplification , Brand Evangelist Index , Customer Lifetime Value and so on and so forth. Inconsistent blog, Twitter, anything, publishing schedule. " 19.

Marketing 126

Marketing Measurement Metrics Testing 126

AWS Big Data

OCTOBER 11, 2023

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.

Management 107

Management Metadata Analytics Dashboards 107

O'Reilly on Data

MAY 27, 2020

In 2001, just as the Lexile system was rolling out state-wide, a professor of education named Stephen Krashen took to the pages of the California School Library Journal to raise an alarm. This whole scoring system also changes the story about who librarians and teachers are.

Risk 355

Risk Testing Reporting Measurement 355

Domino Data Lab

JULY 22, 2019

You know, typically, when you think about running projects, running teams, in terms of setting the priorities for projects, in terms of describing, what are the key metrics for success for a project, that usually falls on product management. I can point to the year 2001. The fourth point is something that surprised us completely.

Data Science 109

Data Science Machine Learning Data Governance Modeling 109

Domino Data Lab

MAY 20, 2021

Working with highly imbalanced data can be problematic in several aspects: Distorted performance metrics — In a highly imbalanced dataset, say a binary dataset with a class ratio of 98:2, an algorithm that always predicts the majority class and completely ignores the minority class will still be 98% correct. return synthetic. References.

Machine Learning 136

Machine Learning Metrics Data mining Knowledge Discovery 136