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 101

Insurance Digital transformation Customer Experience Cloud 101

IBM Big Data Hub

DECEMBER 4, 2023

IBM can help insurance companies insert generative AI into their business processes IBM is one of a few companies globally that can bring together the range of capabilities needed to completely transform the way insurance is marketed, sold, underwritten, serviced and paid for.

Insurance 54

Insurance Digital transformation Compliance Cloud 54

IBM Big Data Hub

OCTOBER 30, 2023

IBM, a pioneer in data analytics and AI, offers watsonx.data, among other technologies, that makes possible to seamlessly access and ingest massive sets of structured and unstructured data. AWS’s scalable infrastructure allows for rapid, large-scale implementation, ensuring agility and data security.

Analytics 81

Analytics Retail Cloud Insurance 81

IBM Big Data Hub

FEBRUARY 14, 2024

By infusing AI into IT operations , companies can harness the considerable power of NLP, big data, and ML models to automate and streamline operational workflows, and monitor event correlation and causality determination. AIOps is one of the fastest ways to boost ROI from digital transformation investments.

Artificial Intelligence 85

Artificial Intelligence Retail Unstructured data Insurance 85

IBM Big Data Hub

FEBRUARY 2, 2023

In addition, companies have complex data security requirements. However, over the past decade, a vast array of compliance and security standards, such as SOC2, PCI, HIPAA, and GDPR, have been introduced, and met by cloud providers.

Cloud 56

Cloud Analytics Unstructured data Compliance 56

Collibra

DECEMBER 1, 2020

Data lake management: Prevent a data swamp. A data lake is a storage repository that holds a vast amount of raw data in its native format, including structured, semi-structured and unstructured data. The data structure and requirements are not defined until the data is needed.

Government 59

Government Analytics Marketing Unstructured data 59