Data Quality, Metrics and Uncertainty

Data Quality

Metrics

Uncertainty

What you need to know about product management for AI

O'Reilly on Data

MARCH 31, 2020

Machine learning adds uncertainty. Underneath this uncertainty lies further uncertainty in the development process itself. There are strategies for dealing with all of this uncertainty–starting with the proverb from the early days of Agile: “ do the simplest thing that could possibly work.”

Management

Management Machine Learning Experimentation Metrics

AI Product Management After Deployment

O'Reilly on Data

OCTOBER 13, 2020

Ideally, AI PMs would steer development teams to incorporate I/O validation into the initial build of the production system, along with the instrumentation needed to monitor model accuracy and other technical performance metrics. But in practice, it is common for model I/O validation steps to be added later, when scaling an AI product.

Management

Management Machine Learning Metrics Modeling

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Bridging the Gap: How ‘Data in Place’ and ‘Data in Use’ Define Complete Data Observability

DataKitchen

SEPTEMBER 21, 2023

Bridging the Gap: How ‘Data in Place’ and ‘Data in Use’ Define Complete Data Observability In a world where 97% of data engineers report burnout and crisis mode seems to be the default setting for data teams, a Zen-like calm feels like an unattainable dream. What is Data in Use?

Testing

Testing Data Quality Predictive Modeling Metrics

Webinars

Agent Tooling: Connecting AI to Your Tools, Systems & Data

Automation, Evolved: Your New Playbook for Smarter Knowledge Work

Data Talks, CFOs Listen: Why Analytics Is The Key To Better Spend Management

Mastering Apache Airflow® 3.0: What’s New (and What’s Next) for Data Orchestration

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Why HR professionals struggle with big data

CIO Business Intelligence

FEBRUARY 20, 2025

Most use master data to make daily processes more efficient and to optimize the use of existing resources. This is due, on the one hand, to the uncertainty associated with handling confidential, sensitive data and, on the other hand, to a number of structural problems.

Big Data

Big Data Measurement Visualization Machine Learning

Data Teams and Their Types of Data Journeys

DataKitchen

OCTOBER 2, 2023

Data Journeys track and monitor all levels of the data stack, from data to tools to code to tests across all critical dimensions. A Data Journey supplies real-time statuses and alerts on start times, processing durations, test results, and infrastructure events, among other metrics.

Data Quality

Data Quality Testing Uncertainty Data Enablement

Human-centered design and data-driven insights elevate precision in government IT modernization

IBM Big Data Hub

SEPTEMBER 11, 2023

Government executives face several uncertainties as they embark on their journeys of modernization. The pain point tracker clusters the foundational data in which value metrics are then applied. and quality (how does this impact service delivery, business process and data quality?).

Data-driven

Data-driven IT Measurement Cost-Benefit

Product Management for AI

Domino Data Lab

JUNE 23, 2019

Companies with successful ML projects are often companies that already have an experimental culture in place as well as analytics that enable them to learn from data. Ensure that product managers work on projects that matter to the business and/or are aligned to strategic company metrics. That’s another pattern.

Management

Management Machine Learning Experimentation Metrics

How data, automation and AI are transforming Business Process Outsourcing into a competitive advantage

IBM Big Data Hub

JUNE 22, 2023

Manik, VP and senior partner for IBM Consulting, outlined a massive opportunity to strategically redesign the client’s finance operations and payment processing by leveraging AI, data analytics, metrics and automation. “Modern BPO is a creator of growth, differentiation and competitive advantage,” Manik says.

Consulting

Consulting Insurance Finance Uncertainty

Fact-based Decision-making

Peter James Thomas

AUGUST 12, 2018

However, often the biggest stumbling block is a human one, getting people to buy in to the idea that the care and attention they pay to data capture will pay dividends later in the process. These and other areas are covered in greater detail in an older article, Using BI to drive improvements in data quality.

Metrics

Metrics Statistics Data Quality Measurement

What’s New and What’s Next in 2023 for HPC

CIO Business Intelligence

JANUARY 4, 2023

Modern data analytics spans a range of technologies, from dedicated analytics platforms and databases to deep learning and artificial intelligence (AI). Ready to evolve your analytics strategy or improve your data quality? Just starting out with analytics? There’s always room to grow, and Intel is ready to help.

Cost-Benefit

Cost-Benefit Machine Learning Uncertainty Modeling

Measuring Validity and Reliability of Human Ratings

The Unofficial Google Data Science Blog

JULY 18, 2023

Once we’ve answered that, we will then define and use metrics to understand the quality of human-labeled data, along with a measurement framework that we call Cross-replication Reliability or xRR. Last, we’ll provide a case study of how xRR can be used to measure improvements in a data-labeling platform.

Measurement

Measurement Metrics Uncertainty Slice and Dice

Data Science, Past & Future

Domino Data Lab

JULY 22, 2019

One is data quality, cleaning up data, the lack of labelled data. 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.

Data Science

Data Science Machine Learning Data Governance Modeling

CIO hiring on the rise: How to land a top tech exec role in 2025

CIO Business Intelligence

FEBRUARY 25, 2025

Typically, election years bring fear, uncertainty, and doubt, causing a slowdown in hiring, Doyle says. Still, many organizations arent yet ready to fully take advantage of AI because they lack the foundational building blocks around data quality and governance. Stories and metrics matter.

Uncertainty

Uncertainty Cost-Benefit Data-driven Marketing

Comparing Physical Assets to Data Assets

Anmut

APRIL 14, 2025

Condition Visibility : Physical assets can be inspected visually or measured using predefined metrics. Condition Complexity : Unlike physical assets, data condition issues are often intangible. Missing context, ambiguity in business requirements, and a lack of accessibility makes tackling data issues complex.

Uncertainty

Uncertainty Data Quality Business Objectives Measurement

Data Leaders Brief

What you need to know about product management for AI

AI Product Management After Deployment

Webinars

Trending Sources

Bridging the Gap: How ‘Data in Place’ and ‘Data in Use’ Define Complete Data Observability

Webinars

Why HR professionals struggle with big data

Data Teams and Their Types of Data Journeys

Human-centered design and data-driven insights elevate precision in government IT modernization

Product Management for AI

How data, automation and AI are transforming Business Process Outsourcing into a competitive advantage

Fact-based Decision-making

What’s New and What’s Next in 2023 for HPC

Measuring Validity and Reliability of Human Ratings

Data Science, Past & Future

CIO hiring on the rise: How to land a top tech exec role in 2025

Comparing Physical Assets to Data Assets

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