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Snowflake’s Performance Optimizations Help ESO Reduce Costs by 60%

Snowflake

ESO’s customers—first responders, ambulatory transporters, hospitals, fire departments, and regulatory bodies—use ESO’s software to document and share a caller’s journey from the time they call 911 through their discharge at the end of the emergency.

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How to Use Kafka for Event Streaming in a Microservices Architecture?

Workfall

It enables real-time data processing, transformation, and analysis by integrating with stream processing frameworks like Apache Spark, Apache Flink, or Kafka Streams, making it a powerful tool for building data pipelines and real-time analytics applications. acl-service.module.ts: Kafka uses the TCP transport layer.

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Using DynamoDB Single-Table Design with Rockset

Rockset

Having supported numerous DynamoDB users through the development and productionization of their real-time analytics applications, we've detailed several methods for organizing your DynamoDB single table model in Rockset, so you can select the design that works best for your specific use case.

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Introduction To Artificial Intelligence In Business | Meaning, Applications, Examples

U-Next

While people are required to provide context and comprehend intricate circumstances, data science benefits from less inaccuracy, enabling more accurate estimates and data analytics. . Applications of AI in Business Operations . Examples of AI applications in Business . Smart Assistants .

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Top Business Intelligence Platforms of 2024 [with Features]

Knowledge Hut

Given its status as one of the complete all-in-one analytics and BI systems available currently, the platform requires some getting accustomed to. Some key features include business intelligence, enterprise planning, and analytics application. You will also need an ETL tool to transport data between each tier.

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Data Mesh Architecture: Revolutionizing Event Streaming with Striim

Striim

The four data mesh principles aim to solve major difficulties that have plagued data and analytics applications for a long time. Additionally, the decentralized data storage model reduces the time to value for data consumers by eliminating the need to transport data to a central store to power analytics.

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Making Sense of Real-Time Analytics on Streaming Data, Part 1: The Landscape

Rockset

It has expanded to various industries and applications, including IoT sensor data, financial data, web analytics, gaming behavioral data, and many more use cases. This type of data has become an essential component of real-time analytics applications because reacting to events quickly can have major effects on a business’ revenue.

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