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Adding New Capabilities for Real-Time Analytics to Azure IoT

ScaleOut Software

The population of intelligent IoT devices is exploding, and they are generating more telemetry than ever. The Microsoft Azure IoT ecosystem offers a rich set of capabilities for processing IoT telemetry, from its arrival in the cloud through its storage in databases and data lakes.

IoT 52
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What is Greenplum Database? Intro to the Big Data Database

Scalegrid

Greenplum Database is an open-source , hardware-agnostic MPP database for analytics, based on PostgreSQL and developed by Pivotal who was later acquired by VMware. This feature-packed database provides powerful and rapid analytics on data that scales up to petabyte volumes. Let’s walk through the top use cases for Greenplum: Analytics.

Big Data 321
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What is observability? Not just logs, metrics and traces

Dynatrace

Many organizations also adopt an observability solution to help them detect and analyze the significance of events to their operations, software development life cycles, application security, and end-user experiences. Making observability actionable and scalable for IT teams.

Metrics 363
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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. We are increasingly surrounded by intelligent IoT devices, which have become an essential part of our lives and an integral component of business and industrial infrastructures. The list goes on.

IoT 78
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Digital Twins Enable Seamless Use of Edge Computing in IoT

ScaleOut Software

Digital twins are software abstractions that track the behavior of individual devices in IoT applications. They combine an event handling function with state information about each device. Also, the use of digital twins provides automatic correlation of incoming events for each device, thereby simplifying applications.

IoT 45
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Digital Twins Enable Seamless Use of Edge Computing in IoT

ScaleOut Software

Digital twins are software abstractions that track the behavior of individual devices in IoT applications. They combine an event handling function with state information about each device. Also, the use of digital twins provides automatic correlation of incoming events for each device, thereby simplifying applications.

IoT 40
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Object-Oriented Programming Simplifies Digital Twins

ScaleOut Software

This model organizes key information about each data source (for example, an IoT device, e-commerce shopper, or medical patient) in a software component that tracks the data source’s evolving state and encapsulates algorithms, such as predictive analytics, for interpreting that state and generating real-time feedback.