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How generative AI delivers value to insurance companies and their customers

IBM Big Data Hub

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.

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5 misconceptions about cloud data warehouses

IBM Big Data Hub

The rise of cloud has allowed data warehouses to provide new capabilities such as cost-effective data storage at petabyte scale, highly scalable compute and storage, pay-as-you-go pricing and fully managed service delivery. In 2021, cloud databases accounted for 85% 1 of the market growth in databases.

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The most valuable AI use cases for business

IBM Big Data Hub

Voice-based queries use natural language processing (NLP) and sentiment analysis for speech recognition so their conversations can begin immediately. Healthcare The healthcare industry is using intelligent automation with NLP to provide a consistent approach to data analysis, diagnosis and treatment.

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Measure Twice, Cut Once: How the Right Data Modeling Tool Drives Business Value

erwin

For decades, data modeling has provided the optimal way to design and deploy new relational databases with high-quality data sources and support application development. In today’s hyper-competitive, data-driven business landscape , organizations are awash with data and the applications, databases and schema required to manage it.

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The 7 most common data quality issues

Collibra

In this blog post, let’s discuss some of the most common data quality issues and how we can tackle them. . Duplicate data. Modern organizations face an onslaught of data from all directions – local databases, cloud data lakes, and streaming data. Data Downtime. Data quality problem statement.