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Building an Optimized Data Pipeline on Azure Using Spark, Data Factory, Databricks, and Synapse Analytics

DZone

Data processing in the cloud has become increasingly popular due to its scalability, flexibility, and cost-effectiveness. Ingesting Data With Azure Data Factory Azure Data Factory is a cloud-based data integration service enabling you to ingest data from various sources into a cloud-based data lake or warehouse.

Azure 246
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Artificial Intelligence in Cloud Computing

Scalegrid

This article delves into the specifics of how AI optimizes cloud efficiency, ensures scalability, and reinforces security, providing a glimpse at its transformative role without giving away extensive details. Predictive analytics, powered by AI, enhance business processes and optimize resource allocation according to workload demands.

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Designing Instagram

High Scalability

We will use a graph database such as Neo4j to store the information. Additionally, we can use columnar databases like Cassandra to store information like user feeds, activities, and counters. Sample Queries supported by Graph Database. System Components. Component Design. Posting on Instagram. API Design. Data Models.

Design 334
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Why Use “Real-Time Digital Twins” for Streaming Analytics?

ScaleOut Software

And how are they different from streaming pipelines like Azure Stream Analytics and Apache Flink/Beam? What Problems Does Streaming Analytics Solve? To understand why we need real-time digital twins for streaming analytics, we first need to look at what problems are tackled by popular streaming platforms.

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Deploying Real-Time Digital Twins On Premises with ScaleOut StreamServer DT

ScaleOut Software

With the ScaleOut Digital Twin Streaming Service , an Azure-hosted cloud service, ScaleOut Software introduced breakthrough capabilities for streaming analytics using the real-time digital twin concept. Scaleout StreamServer® DT was created to meet this need.

IoT 52
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The Need for Real-Time Device Tracking

ScaleOut Software

Real-Time Device Tracking with In-Memory Computing Can Fill an Important Gap in Today’s Streaming Analytics Platforms. The Limitations of Today’s Streaming Analytics. How are we managing the torrent of telemetry that flows into analytics systems from these devices? The list goes on.

IoT 78
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The Amazing Evolution of In-Memory Computing

ScaleOut Software

In general terms, in-memory computing refers to the related concepts of (a) storing fast-changing data in primary memory instead of in secondary storage and (b) employing scalable computing techniques to distribute a workload across a cluster of servers.