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Optimizing a Centralized Approach for the Modern Distributed Data Estate

CIO Business Intelligence

billion connected Internet of Things (IoT) devices by 2025, generating almost 80 billion zettabytes of data at the edge. This next manifestation of centralized data strategy emanates from past experiences with trying to coalesce the enterprise around a large-scale monolithic data lake. over last year.

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

AWS Big Data

A data hub contains data at multiple levels of granularity and is often not integrated. It differs from a data lake by offering data that is pre-validated and standardized, allowing for simpler consumption by users. Data hubs and data lakes can coexist in an organization, complementing each other.

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Better, faster decisions: Why businesses thrive on real-time data

CIO Business Intelligence

We’ve all experienced the pain of what continues to happen with the disconnect between customer usage metrics and gaps in supply chain data.” — Frank Cutitta ( @fcutitta ), CEO and Founder, HealthTech Decisions Lab “Operationally, think of logistics.

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Reference guide to build inventory management and forecasting solutions on AWS

AWS Big Data

Such a solution should use the latest technologies, including Internet of Things (IoT) sensors, cloud computing, and machine learning (ML), to provide accurate, timely, and actionable data. However, analyzing large volumes of data can be a time-consuming and resource-intensive task. This is where Athena come in.

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Architectural patterns for real-time analytics using Amazon Kinesis Data Streams, part 1

AWS Big Data

For example, you can use Amazon Kinesis Managed Service for Apache Flink for advanced streaming use cases with multiple streaming destinations and complex stateful stream processing or if you want to monitor business metrics in real time (such as every hour). Lambda is good for event-based and stateless processing.

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Amazon Kinesis Data Streams: celebrating a decade of real-time data innovation

AWS Big Data

Ten years ago, we launched Amazon Kinesis Data Streams , the first cloud-native serverless streaming data service, to serve as the backbone for companies, to move data across system boundaries, breaking data silos. Next, let’s go back to the NHL use case where they combine IoT, data streaming, and machine learning.

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

Corinium

Life insurance needs accurate data on consumer health, age and other metrics of risk. And it’s become a hyper-competitive business, so enhancing customer service through data is critical for maintaining customer loyalty. And more recently, we have also seen innovation with IOT (Internet Of Things).

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