Domino Data Lab

JULY 22, 2019

By virtue of that, if you take those log files of customers interactions, you aggregate them, then you take that aggregated data, run machine learning models on them, you can produce data products that you feed back into your web apps, and then you get this kind of effect in business. That was the origin of big data.

Data Science 109

Data Science Machine Learning Data Governance Modeling 109

IBM Big Data Hub

FEBRUARY 22, 2024

Defense leaders focused on operationalizing the responsible curation of AI must first agree upon a shared vocabulary—a common culture that guides safe, responsible use of AI—before they implement technological solutions and guardrails that mitigate risk. Data interpretation takes practice and is an interdisciplinary effort.

Metadata 101

Metadata Measurement Risk Modeling 101

Cloudera

JANUARY 22, 2019

In conjunction with the evolving data ecosystem are demands by business for reliable, trustworthy, up-to-date data to enable real-time actionable insights. Big Data Fabric has emerged in response to modern data ecosystem challenges facing today’s enterprises. What is Big Data Fabric? Data access.

Big Data 44

Big Data Data Lake Internet of Things Enterprise 44

Alation

MARCH 21, 2023

To fully realize data’s value, organizations in the travel industry need to dismantle data silos so that they can securely and efficiently leverage analytics across their organizations. What is big data in the travel and tourism industry? Otherwise, they risk a data privacy violation.

Data Analytics 52

Data Analytics Analytics Data-driven Big Data 52

O'Reilly on Data

MARCH 20, 2019

Like many others, I’ve known for some time that machine learning models themselves could pose security risks. An attacker could use an adversarial example attack to grant themselves a large loan or a low insurance premium or to avoid denial of parole based on a high criminal risk score. Newer types of fair and private models (e.g.,

Modeling 222

Modeling Machine Learning Predictive Modeling Consulting 222

Domino Data Lab

AUGUST 8, 2019

I mention this here because there was a lot of overlap between current industry data governance needs and what the scientific community is working toward for scholarly infrastructure. The gist is, leveraging metadata about research datasets, projects, publications, etc., 2018 – Global reckoning about data governance, aka “Oops!…We

Data Science 71

Data Science Machine Learning Data Governance Statistics 71

Cloudera

FEBRUARY 11, 2019

Covering just one type of analytics and integrated with one or two other applications, organizations are still faced with a patchwork of siloed systems that each carry their own data, metadata, security, and governance. The problem is only amplified as organizations start leveraging cloud and transient workloads.

Digital Transformation 56

Digital Transformation Data Governance Data Warehouse Data-driven 56

O'Reilly on Data

MAY 21, 2019

For example, in a July 2018 survey that drew more than 11,000 respondents, we found strong engagement among companies: 51% stated they already had machine learning models in production. With all the hype around AI, it can be tempting to jump into use cases involving data types with which you aren’t familiar. Source: O'Reilly.

Machine Learning 238

Machine Learning Technology Deep Learning Data Science 238