CIO Business Intelligence

JUNE 13, 2022

As with all financial services technologies, protecting customer data is extremely important. In some parts of the world, companies are required to host conversational AI applications and store the related data on self-managed servers rather than subscribing to a cloud-based service. Just starting out with analytics?

Data Processing 102

Data Processing Deep Learning Insurance Cost-Benefit 102

O'Reilly on Data

FEBRUARY 4, 2019

In a recent survey , we explored how companies were adjusting to the growing importance of machine learning and analytics, while also preparing for the explosion in the number of data sources. As interest in machine learning (ML) and AI grow, organizations are realizing that model building is but one aspect they need to plan for.

Machine Learning 277

Machine Learning Enterprise IoT Big Data 277

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 307

Testing Machine Learning Consulting Data Quality 307

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. That’s where remediation strategies come in. We discuss seven remediation strategies below. Data augmentation.

Machine Learning 191

Machine Learning Modeling Testing Risk Management 191

IBM Big Data Hub

NOVEMBER 14, 2023

Data monetization strategy: Managing data as a product Every organization has the potential to monetize their data; for many organizations, it is an untapped resource for new capabilities. Generative AI has only served to accelerate the options for data product design, lifecycle delivery and operational management.

Strategy 115

Strategy Cost-Benefit Data-driven Measurement 115

Domino Data Lab

APRIL 3, 2019

The longer answer is that in the context of machine learning use cases, strong assumptions about data integrity lead to brittle solutions overall. So we had three tiers providing a separation of concerns: presentation, logic, data. Andrew Ng later described this strategy as the “Virtuous Cycle of AI” – a.k.a.

Data Governance 84

Data Governance Machine Learning Metadata Big Data 84

IBM Big Data Hub

OCTOBER 20, 2023

Artificial intelligence platforms enable individuals to create, evaluate, implement and update machine learning (ML) and deep learning models in a more scalable way. AI platform tools enable knowledge workers to analyze data, formulate predictions and execute tasks with greater speed and precision than they can manually.

Machine Learning 80

Machine Learning Manufacturing Cost-Benefit Deep Learning 80