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

Jet Global

NOVEMBER 15, 2019

Despite the fact that massive amounts of information lives inside this solution, PeopleSoft reporting is a cumbersome process, mostly because the data are poorly integrated. Members of the finance or IT teams have to go hunting through multiple data sources, identifying and integrating the metrics they need to build reports.

Reporting 75

Reporting Uncertainty Metrics Finance 75

Jet Global

JANUARY 22, 2020

Much of the financial reporting process, including data collection, integration, analysis, and visualization, can now run on autopilot. Contending with Data Errors. Any reporting process that relies on users manually manipulating data is at risk of typos and other human errors compromising that data.

Reporting 78

Reporting Snapshot Data-driven Uncertainty 78

Darkhorse

MARCH 31, 2015

Add to these all of the decisions that they could be making (but aren’t) because of uncertainty or laziness. We’ll do so by eliminating those with high risk in data inputs, research, and implementation. Remind them that your solutions won’t tell them what to do, but will simply reduce uncertainty. That’s a good thing.

Uncertainty 45

Uncertainty Data-driven Consulting Metrics 45

IBM Big Data Hub

SEPTEMBER 11, 2023

Government executives face several uncertainties as they embark on their journeys of modernization. A pain point tracker (a repository of business, human-centered design and technology issues that inhibit users’ ability to execute critical tasks) captures themes that arise during the data collection process.

Data-driven 91

Data-driven IT Measurement Cost-Benefit 91

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. They’re being told they have to embrace uncertainty.

Data Science 109

Data Science Machine Learning Data Governance Modeling 109

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