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 176

Testing Data Quality Predictive Modeling Metrics 176

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 100

Data Quality Testing Uncertainty Data Enablement 100

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 332

Management Machine Learning Experimentation Metrics 332

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 49

Metrics Statistics Data Quality Measurement 49

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 110

Management Machine Learning Experimentation Metrics 110

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 90

Data-driven IT Measurement Cost-Benefit 90

Domino Data Lab

JULY 22, 2019

What I’m trying to say is this evolution of system architecture, the hardware driving the software layers, and also, the whole landscape with regard to threats and risks, it changes things. You see these drivers involving risk and cost, but also opportunity. One is data quality, cleaning up data, the lack of labelled data.

Data Science 109

Data Science Machine Learning Data Governance Modeling 109