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Commercial Lines Insurance- the End of the Line for All Data

Cloudera

I’ve had the pleasure to participate in a few Commercial Lines insurance industry events recently and as a prior Commercial Lines insurer myself, I am thrilled with the progress the industry is making using data and analytics. Another historic example is crop and livestock insurance in Germany in the 1700s.

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How intelligent document processing automates content-intensive processes

CIO Business Intelligence

Gartner estimates unstructured content makes up 80% to 90% of all new data and is growing three times faster than structured data 1. The ability to effectively wrangle all that data can have a profound, positive impact on numerous document-intensive processes across enterprises.

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CIOs worry about Gen AI – for all the right reasons

CIO Business Intelligence

And in insurance, according to Alex Cook, Head of Strategic Capabilities at New York Life Insurance Co. The insurer is developing an AI-based tool to help customer service reps better field wide-ranging questions about complex issues. Did we solve the problem? How many times did they have to call? LLMs pick that up on their own.

Insurance 131
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Salesforce debuts Zero Copy Partner Network to ease data integration

CIO Business Intelligence

Zero-copy integration eliminates the need for manual data movement, preserving data lineage and enabling centralized control fat the data source. Currently, Data Cloud leverages live SQL queries to access data from external data platforms via zero copy. Ground generative AI.

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Build a decentralized semantic search engine on heterogeneous data stores using autonomous agents

AWS Big Data

Run the notebook There are six major sections in the notebook: Prepare the unstructured data in OpenSearch Service – Download the SEC Edgar Annual Financial Filings dataset and convert the company financial filing document into vectors with Amazon Titan Text Embeddings model and store the vector in an Amazon OpenSearch Service vector database.

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The Missing Link in Enterprise Data Governance: Metadata

Octopai

Steve, the Head of Business Intelligence at a leading insurance company, pushed back in his office chair and stood up, waving his fists at the screen. We’re dealing with data day in and day out, but if isn’t accurate then it’s all for nothing!” Why aren’t the numbers in these reports matching up? Automated metadata governance.

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Big Data Ingestion: Parameters, Challenges, and Best Practices

datapine

Consumer data: Data transmitted by customers including, banking records, banking data, stock market transactions, employee benefits, insurance claims, etc. Operations data: Data generated from a set of operations such as orders, online transactions, competitor analytics, sales data, point of sales data, pricing data, etc.

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