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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. Commercial Lines truly is an “uber industry” with respect to data. A Long, Long Time Ago.

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Quantitative and Qualitative Data: A Vital Combination

Sisense

Digging into quantitative data Why is quantitative data important What are the problems with quantitative data Exploring qualitative data Qualitative data benefits Getting the most from qualitative data Better together. Almost every modern organization is now a data-generating machine. or “how often?”

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Exploring real-time streaming for generative AI Applications

AWS Big Data

FMs are multimodal; they work with different data types such as text, video, audio, and images. Large language models (LLMs) are a type of FM and are pre-trained on vast amounts of text data and typically have application uses such as text generation, intelligent chatbots, or summarization.

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The Power of Ontologies and Knowledge Graphs: Practical Examples from the Financial Industry

Ontotext

Knowledge Representation In the context of the Financial Services Industry domain, the most popular examples of such data are entity (Who?) These two key data elements are used in approximately 80% of the use cases in the sector. Integrating reporting to move to a more streamlined, efficient approach to data collection.

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What is a Data Pipeline?

Jet Global

A data pipeline is a series of processes that move raw data from one or more sources to one or more destinations, often transforming and processing the data along the way. Data pipelines support data science and business intelligence projects by providing data engineers with high-quality, consistent, and easily accessible data.