Cloudera

SEPTEMBER 7, 2023

With the emergence of new creative AI algorithms like large language models (LLM) fromOpenAI’s ChatGPT, Google’s Bard, Meta’s LLaMa, and Bloomberg’s BloombergGPT—awareness, interest and adoption of AI use cases across industries is at an all time high. But it’s also fraught with risk.

Insurance 80

Insurance Risk Data-driven Finance 80

Cloudera

NOVEMBER 16, 2022

Tracks represented financial services, insurance, retail and consumer packaged goods, and healthcare. Overall, it struck me that while data science is not new, most firms are still defining the mission of the data office and data officer. Successes are real, but getting there takes creativity and fortitude.

Insurance 79

Insurance Cost-Benefit Metrics Measurement 79

Cloudera

JANUARY 5, 2023

In the past year, businesses who doubled down on digital transformation during the pandemic saw their efforts coming to fruition in the form of cost savings and more streamlined data management. 1- Treating data as a strategic business asset . 2- Operationalizing adaptive AI systems for quicker business decision-making.

Cost-Benefit 52

Cost-Benefit Business Objectives Machine Learning Data Architecture 52

IBM Big Data Hub

DECEMBER 1, 2023

Insurers struggle to manage profitability while trying to grow their businesses and retain clients. Large, well-established insurance companies have a reputation of being very conservative in their decision making, and they have been slow to adopt new technologies.

Insurance 108

Insurance Digital Transformation Unstructured Data Risk 108

IBM Big Data Hub

JULY 17, 2023

The watsonx platform has three components: watsonx.ai (now available), watsonx.data (now available) and watsonx.governance (expected availability in November). How can you get started today? With watsonx.ai, businesses can effectively train, validate, tune and deploy AI models with confidence and at scale across their enterprise.

Machine Learning 68

Machine Learning Data Warehouse Modeling Cost-Benefit 68

Alation

FEBRUARY 10, 2022

Data classification is necessary for leveraging data effectively and efficiently. Effective data classification helps mitigate risk, maintain governance and compliance, improve efficiencies, and help businesses understand and better use data. Manual Data Classification. Automated Data Classification.

Data Governance 52

Data Governance Risk Insurance Strategy 52