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 290

Strategy Experimentation Uncertainty Machine Learning 290

Cloudera

AUGUST 26, 2021

Learn more about the impacts of global data sharing in this blog, The Ethics of Data Exchange. Before we jump into the data ingestion step, here is a quick overview of how Ozone manages its metadata namespace through volumes, buckets and keys. . Data ingestion through ‘s3’. label="uncertainty").

Data Science 113

Data Science Forecasting Metadata Machine Learning 113

Rocket-Powered Data Science

JULY 19, 2023

That is not a totally clear separation and distinction, but it might help to clarify their different applications of data science. Data scientists work with business users to define and learn the rules by which precursor analytics models produce high-accuracy early warnings.

Data-driven 188

Data-driven Enterprise Analytics Machine Learning 188

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

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. They don’t have the resources they need to clean up data quality problems. And that’s just the beginning. Respondent demographics.

Data Quality 311

Data Quality Metadata Data Governance Publishing 311

Domino Data Lab

JUNE 2, 2019

Co-chair Paco Nathan provides highlights of Rev 2 , a data science leaders summit. We held Rev 2 May 23-24 in NYC, as the place where “data science leaders and their teams come to learn from each other.” If you lead a data science team/org, DM me and I’ll send you an invite to data-head.slack.com ”.

Data-driven 110

Data-driven Data Science Machine Learning Modeling 110