O'Reilly on Data

FEBRUARY 4, 2019

In this post, I’ll describe some of the key areas of interest and concern highlighted by respondents from Europe, while describing how some of these topics will be covered at the upcoming Strata Data conference in London (April 29 - May 2, 2019). Data Platforms. Data Integration and Data Pipelines.

Machine Learning 277

Machine Learning Enterprise IoT Big Data 277

O'Reilly on Data

DECEMBER 12, 2019

Security vulnerabilities : adversarial actors can compromise the confidentiality, integrity, or availability of an ML model or the data associated with the model, creating a host of undesirable outcomes. Privacy harms : models can compromise individual privacy in a long (and growing) list of ways. [8]

Machine Learning 191

Machine Learning Modeling Testing Risk Management 191

DataKitchen

APRIL 13, 2021

RightData – A self-service suite of applications that help you achieve Data Quality Assurance, Data Integrity Audit and Continuous Data Quality Control with automated validation and reconciliation capabilities. QuerySurge – Continuously detect data issues in your delivery pipelines.

Testing 300

Testing Machine Learning Consulting Data Quality 300

Domino Data Lab

APRIL 3, 2019

Data governance shows up as the fourth-most-popular kind of solution that enterprise teams were adopting or evaluating during 2019. That’s a lot of priorities – especially when you group together closely related items such as data lineage and metadata management which rank nearby. We keep feeding the monster data.

Data Governance 84

Data Governance Machine Learning Metadata Big Data 84