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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.
Blockchain Blockchain
Cloud technologies Cloud technologies
Data integration tools Data integration tools
Decision management Decision management
In-memory computing In-memory computing
Intelligent integration and BPM Intelligent integration and BPM
IIC Testbeds IIC Testbeds
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From BI to Real-Time Intelligence: White Paper

From BI to Real-Time Intelligence: White Paper

Fast data can’t sit in a warehouse.

Written By

RTInsights Team

Feb 9, 2016

In a world where financial transactions, e-commerce, and IoT communications all take place in an instant, the ability to ingest and analyze this data is critical to a business. But business intelligence (BI) systems, built on the old data warehouse model, move too slowly to ingest and analyze such data. What’s needed is a computing and analytic architecture that enables instant analysis on streaming data for operational intelligence.

In this white paper you will learn:

The differences between BI and operational intelligence
Different technologies for real-time data ingestion
Seven applications for operational intelligence, ranging from the IoT to finance and healthcare.

Want more? Check out our most-read content:

White Paper: How to ‘Future-Proof’ a Streaming Analytics Platform
Research from Gartner: Real-Time Analytics with the Internet of Things
E-Book: How to Move to a Fast Data Architecture
The Value of Bringing Analytics to the Edge
What’s Your Business Intelligence System? How About Your Culture
Video: Rocana Rolls Out 1TB of Free IT Monitoring
The Value of Bringing Analytics to the Edge

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Real-time Analytics News for the Week Ending March 7

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Real-time Analytics News for the Week Ending March 7

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Real-time Analytics News for the Week Ending February 28

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IBM’s New Acquisition Highlights Organizations Aren’t Ready for Real-Time

IBM’s New Acquisition Highlights Organizations Aren’t Ready for Real-Time

The IBM acquisition of Confluent is indicative of the tech world’s fixation on real-time data streaming. However, the more pressing issue is the overwhelming volume of unstructured documents that hold the critical context that real-time AI often overlooks.

Feb 24, 2026

Real-time Analytics News for the Week Ending February 21

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In this week’s real-time analytics news: The European Commission prods the creation of frontier general-purpose AI systems.

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Featured Resources from Cloud Data Insights

Engineering the Agentic Enterprise: Building Smarter, Adaptive, Autonomous Systems

Artificial intelligence technologies

Engineering the Agentic Enterprise: Building Smarter, Adaptive, Autonomous Systems

The transition to a truly agentic enterprise is not merely an IT upgrade. Such a transition is an architectural and philosophical metamorphosis. The organizations that scale with confidence are those that recognize this early.

Mar 10, 2026

The AI That Actually Scales Is Boring. That’s the Point.

Artificial intelligence technologies

The AI That Actually Scales Is Boring. That’s the Point.

Boring AI earns trust because it works. It removes friction from daily tasks, and over time, that trust becomes the foundation for more ambitious systems.

Mar 9, 2026

Real-time Analytics News for the Week Ending March 7

Artificial intelligence technologies

Real-time Analytics News for the Week Ending March 7

In this week’s real-time analytics news: IBM launched Db2 Genius Hub, which brings autonomous capabilities to Db2.

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The State of the Neoclouds Market

The State of the Neoclouds Market

Neoclouds offer performance specialization, which increasingly is factored into what some call multi-compute strategies. In general, what that means is that enterprises are using hyperscalers for general workloads, neoclouds for model training, and edge infrastructure for inference.

Salvatore Salamone

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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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