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Link to Best Practices for Deploying and Scaling Industrial AI

Best Practices for Deploying and Scaling Industrial AI

Artificial Intelligence (AI) is transforming industrial operations, helping organizations optimize workflows, reduce downtime, and enhance productivity. Different industry verticals leverage AI in unique ways.

Link to The Center for Adaptive Edge Intelligence

The Center for Adaptive Edge Intelligence

Adaptive edge intelligence brings real-time decision-making to the point of data creation, whether from sensors, machines, or cameras.

Link to The Value of Vehicle Electrification

The Value of Vehicle Electrification

Electric vehicles (EVs) present automakers with many design, engineering, and manufactu ring challenges.

Link to Accelerating Manufacturing Digital Transformation with Industrial Connectivity and IoT

Accelerating Manufacturing Digital Transformation with Industrial Connectivity and IoT

Digital transformation is empowering industrial organizations to deliver sustainable innovation, disruption-proof products and services, and continuous operational improvement.

Link to Smart Manufacturing for Automotive

Smart Manufacturing for Automotive

Leading a transportation revolution in autonomous, electric, shared mobility and connectivity with the next generation of design and development tools.

Link to Center for Data Pipeline Automation

Center for Data Pipeline Automation

As businesses become data-driven and rely more heavily on analytics to operate, getting high-quality, trusted data to the right data user at the right time is essential.

Link to Center for Automated Integration

Center for Automated Integration

The goal of automated integration is to enable applications and systems that were built separately to easily share data and work together, resulting in new capabilities and efficiencies that cut costs, uncover insights, and much more.

Link to Continuous Intelligence: Insights

Continuous Intelligence: Insights

Digital transformation requires continuous intelligence (CI). Today's digital businesses are leveraging this new category of software which includes real-time analytics and insights from a single, cloud-native platform across multiple use cases to speed decision-making, and drive world-class customer experiences.
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Use Cases for Real-Time Streaming Analytics (white paper)

Use Cases for Real-Time Streaming Analytics (white paper)

streaming analytics use cases

Where’s the business value in real-time streaming analytics?

Written By

RTInsights Team

Mar 28, 2016

3 minute read

Technology now exists to capture real-time data from a wide variety of sources, including Internet of Things devices, mobile phones, web browsing, and financial transactions. But that data remains largely unused by most businesses.

Real-time streaming analytics looks to harness value from that data. In this white paper from Impetus Technologies, you will learn:

Why real-time streaming analytics is necessary.
Key use cases for real-time streaming analytics for industry verticals.
Horizontal applications such as customer experience, IoT analytics, and marketing.

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Want more? Check out our most-read content:

Intelligent Business Operations: White Paper
7 Essential Elements in a Real-Time Streaming Analytics Platform
Fog Computing: A Reference Architecture
Why Edge Computing Is Here to Stay: Five Use Cases
A Business Intelligence Strategy for Real-Time Analytics
Why IoT Edge Computing Is Crucial

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Every transaction, order, customer interaction, and internal operation depends on decisions. At a time when businesses are under pressure to improve efficiencies, cut costs, and be more responsive, automating decisions becomes essential. While many businesses have picked off the low-hanging fruit when automating, most need to add more. Specifically, businesses want to automate complex decisions, involving multiple steps, multiple data sources and many rules.

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AI Workload Accelerators: Which Gives You the Biggest Bang for the Buck?

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Real-Time Decisions

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AI is changing the way data is accessed and used. Organizations that don’t rethink their data architecture will be left behind. AI is changing the way data is accessed and used.

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The Next AI Revolution Isn’t Generative. It’s Adaptive.

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The Q2 Mandate: Why AI’s Biggest Hurdle is Leadership, Not Technology

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Analysis and market insights on real-time analytics including Big Data, the IoT, and cognitive computing. Business use cases and technologies are discussed.

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