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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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How To Choose Analytics Software: Free Guide

How To Choose Analytics Software: Free Guide

choosing analytics software

First, focus on the business decisions to be made.

Written By

RTInsights Team

Mar 19, 2017

Deciding where and when to deploy analytics software in an enterprise can be challenging.

One way to approach the problem is to adopt a decision-management approach, in which an organization thinks about the decision to be made and who is making that decision.

By focusing on decision-making – roughly the types of decisions to be made, who makes them, and when they need to be made – organizations can identify the right analytics software and infrastructure needs.

In this free guide from James Taylor of Decision Management Solutions, you will learn:

The four basic types of decisions: strategic, tactical, planning, and operations, and how analytics capabilities can help.
Analytic styles, including interactivity, data visualization, and scaling.
Types of analytics, including descriptive, diagnostic, predictive, as well as capabilities that optimize business decisions.
Data types, including structured, semi-structured, and unstructured.
Computing power considerations for analytics, including in-database, in-Hadoop, in-memory, data grids, workstations, and the cloud.

Complete the form to download the report.

RTInsights Team

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Domain-Specific LLMs: How to Make AI Useful for Your Business

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