Andrew White

MAY 4, 2020

COVID-19 and the related economic fallout has pushed organizations to extreme cost optimization decision making with uncertainty. As a result, Data, Analytics and AI are in even greater demand. So conventional wisdom (see second example below) was that you needed to focus heavily on a broad data quality program.

Uncertainty 90

Uncertainty Data Quality Consulting Predictive Modeling 90

Rocket-Powered Data Science

FEBRUARY 15, 2023

Those F’s are: Fragility, Friction, and FUD (Fear, Uncertainty, Doubt). These changes may include requirements drift, data drift, model drift, or concept drift. Here are my 10 rules ( i.e., Business Strategies for Deploying Disruptive Data-Intensive, AI, and ChatGPT Implementations): Honor business value above all other goals.

Strategy 289

Strategy Experimentation Uncertainty Machine Learning 289

Domino Data Lab

JULY 22, 2019

Paco Nathan presented, “Data Science, Past & Future” , at Rev. At Rev’s “ Data Science, Past & Future” , Paco Nathan covered contextual insight into some common impactful themes over the decades that also provided a “lens” help data scientists, researchers, and leaders consider the future.

Data Science 109

Data Science Machine Learning Data Governance Modeling 109

O'Reilly on Data

FEBRUARY 11, 2020

We suspected that data quality was a topic brimming with interest. The responses show a surfeit of concerns around data quality and some uncertainty about how best to address those concerns. Key survey results: The C-suite is engaged with data quality. Adopting AI can help data quality.

Data Quality 304

Data Quality Metadata Data Governance Publishing 304

CIO Business Intelligence

APRIL 28, 2022

However, many financial services companies still prefer to build their own data centers rather than leverage cloud solutions. Much of this reluctance stems from the regulatory environment, arising from lengthy reviews and approvals processes, or even simple near-term regulatory uncertainty. .

Analytics 98

Analytics Insurance Big Data Uncertainty 98

CIO Business Intelligence

JANUARY 4, 2023

In the HPC community, we recognize a need for tools to support machine learning operations and data science management; these tools must be able to scale and integrate with HPC software, compute and storage environments. Ready to evolve your analytics strategy or improve your data quality?

Cost-Benefit 59

Cost-Benefit Machine Learning Modeling Uncertainty 59

O'Reilly on Data

OCTOBER 13, 2020

Therefore, the PM should consider the team that will reconvene whenever it is necessary to build out or modify product features that: ensure that inputs are present and complete, establish that inputs are from a realistic (expected) distribution of the data, and trigger alarms, model retraining, or shutdowns (when necessary).

Management 244

Management Metrics Machine Learning Modeling 244