Rocket-Powered Data Science

FEBRUARY 15, 2023

Third, any commitment to a disruptive technology (including data-intensive and AI implementations) must start with a business strategy. Those F’s are: Fragility, Friction, and FUD (Fear, Uncertainty, Doubt). These changes may include requirements drift, data drift, model drift, or concept drift.

Strategy 289

Strategy Experimentation Uncertainty Machine Learning 289

Jen Stirrup

NOVEMBER 15, 2022

Why do organizations get stuck with their data? Often, this problem can be due to the organization concentrating solely on technology and data. However, organizations can be supported by a synergistic approach by integrating systems thinking with the data strategy and technical perspective. It is such a fundamental question.

Data Science 145

Data Science Digital Transformation Data-driven Measurement 145

O'Reilly on Data

MARCH 31, 2020

AI products are automated systems that collect and learn from data to make user-facing decisions. All you need to know for now is that machine learning uses statistical techniques to give computer systems the ability to “learn” by being trained on existing data. Machine learning adds uncertainty.

Management 332

Management Machine Learning Experimentation Metrics 332

IBM Big Data Hub

SEPTEMBER 11, 2023

Government executives face several uncertainties as they embark on their journeys of modernization. What makes or breaks the success of a modernization is our willingness to develop a detailed, data-driven understanding of the unique needs of those that we aim to benefit.

Data-driven 90

Data-driven IT Measurement Cost-Benefit 90

CIO Business Intelligence

JANUARY 4, 2023

Cloud, sustainability, scale, and exponential data growth—these major factors that set the tone for high performance computing (HPC) in 2022 will also be key in driving innovation for 2023. As leaders in the HPC industry, we are worried about how to cool these data centers. Another big focus is on liquid cooling. [2]

Cost-Benefit 59

Cost-Benefit Machine Learning Modeling Uncertainty 59

Peter James Thomas

AUGUST 12, 2018

These normally appear at the end of an article, but it seemed to make sense to start with them in this case: Recently I published Building Momentum – How to begin becoming a Data-driven Organisation. A number of factors can play into the accuracy of data capture. Honesty of Data that is captured. Timing issues with Data.

Metrics 49

Metrics Statistics Data Quality Measurement 49

Domino Data Lab

JUNE 23, 2019

Skomoroch advocates that organizations consider installing product leaders with data expertise and ML-oriented intuition (i.e., 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. A few highlights from the session include.

Management 110

Management Machine Learning Experimentation Metrics 110