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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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Interview with Dominic Sartorio, Senior Vice President for Products & Development, Protegrity

Corinium

Ahead of the Chief Data Analytics Officers & Influencers, Insurance event we caught up with Dominic Sartorio, Senior Vice President for Products & Development, Protegrity to discuss how the industry is evolving. Are you seeing any specific issues around the insurance industry at the moment that should concern CDAOs?

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How FIS ingests and searches vector data for quick ticket resolution with Amazon OpenSearch Service

AWS Big Data

The workflow includes the following steps: GitHub webhook events stream data to both Amazon S3 and OpenSearch Service, facilitating real-time data analysis. A Lambda function connects to an API Gateway REST API, processing and structuring the received payloads. Want to know more?

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A Flexible and Efficient Storage System for Diverse Workloads

Cloudera

Today’s platform owners, business owners, data developers, analysts, and engineers create new apps on the Cloudera Data Platform and they must decide where and how to store that data. Structured data (such as name, date, ID, and so on) will be stored in regular SQL databases like Hive or Impala databases.

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How to get powerful and actionable insights from any and all of your data, without delay

Cloudera

They were not able to quickly and easily query and analyze huge amounts of data as required. They also needed to combine text or other unstructured data with structured data and visualize the results in the same dashboards. Events or time-series data served by our real-time events or time-series data store solutions.

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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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How gaming companies can use Amazon Redshift Serverless to build scalable analytical applications faster and easier

AWS Big Data

Flexible and easy to use – The solutions should provide less restrictive, easy-to-access, and ready-to-use data. They should also provide optimal performance with low or no tuning. Open file formats enable analysis of the same Amazon S3 data using multiple processing and consumption layer components.