O'Reilly on Data

JULY 28, 2020

Without clarity in metrics, it’s impossible to do meaningful experimentation. AI PMs must ensure that experimentation occurs during three phases of the product lifecycle: Phase 1: Concept During the concept phase, it’s important to determine if it’s even possible for an AI product “ intervention ” to move an upstream business metric.

Marketing 363

Marketing Experimentation Metrics Testing 363

CIO Business Intelligence

FEBRUARY 14, 2024

As the cost of data storage has fallen, many organizations are keeping unnecessary data, or cleaning up data that’s out of date or no longer useful after a migration or reorganization. Do you want to have an even more powerful search capability with AI in your data, and to be unsure about how you’ve organized that data?”

IT 143

IT Metadata Data-driven Management 143

Sanjeev Mohan

FEBRUARY 6, 2019

Then in the middle of 2017, a realization set in that we were one year away from GDPR and needed to focus on data governance. I ended up writing two documents on data governance. As you can tell, data governance is a hot topic but an area that many public cloud vendors are weak in.

Data Analytics 49

Data Analytics Analytics Data Governance Experimentation 49

Cloudera

FEBRUARY 16, 2022

Weak model lineage can result in reduced model performance, a lack of confidence in model predictions and potentially violation of company, industry or legal regulations on how data is used. . Within the CML data service, model lineage is managed and tracked at a project level by the SDX. Figure 03: lineage.yaml.

Machine Learning 85

Machine Learning Modeling Metadata Recreation/Entertainment 85

AWS Big Data

OCTOBER 4, 2023

Collaboration – Analysts, data scientists, and data engineers often own different steps within the end-to-end analytics journey but do not have an simple way to collaborate on the same governed data, using the tools of their choice.

Metadata 101

Metadata Data Lake Publishing Data Governance 101

AWS Big Data

JANUARY 24, 2023

AWS Lake Formation helps with enterprise data governance and is important for a data mesh architecture. It works with the AWS Glue Data Catalog to enforce data access and governance. The utility for cloning and experimentation is available in the open-sourced GitHub repository.

Data Architecture 67

Data Architecture Metadata Data Lake Snapshot 67

O'Reilly on Data

MARCH 18, 2020

Whether it’s controlling for common risk factors—bias in model development, missing or poorly conditioned data, the tendency of models to degrade in production—or instantiating formal processes to promote data governance, adopters will have their work cut out for them as they work to establish reliable AI production lines.

Enterprise 316

Enterprise Deep Learning Data Governance Risk 316