Cloud Hosting

DUBLIN, August 06, 2021--(BUSINESS WIRE)--The "Artificial Intelligence in Big Data Analytics and IoT: Market for Data Capture, Information and Decision Support Services 2021 - 2026" report has been added to ResearchAndMarkets.com's offering.

This report evaluates various AI technologies and their use relative to analytics solutions within the rapidly growing enterprise and industrial data arena. The report assesses emerging business models, leading companies, and solutions.

The report also analyzes how different forms of AI may be best used for problem-solving. The report also evaluates the market for AI in IoT networks and systems. The report provides forecasting for unit growth and revenue for both analytics and IoT from 2021 to 2026.

The Internet of Things (IoT) in consumer, enterprise, industrial, and government market segments has very unique needs in terms of infrastructure, devices, systems, and processes. One thing they all have in common is that they each produce massive amounts of data, most of which is of the unstructured variety, requiring big data technologies for management.

Artificial Intelligence (AI) algorithms enhance the ability for big data analytics and IoT platforms to provide value to each of these market segments. The author sees three different types of IoT Data: (1) Raw (untouched and unstructured) Data, (2) Meta (data about data), and (3) Transformed (valued-added data). Artificial Intelligence (AI) will be useful in support of managing each of these data types in terms of identifying, categorizing, and decision making.

AI coupled with advanced big data analytics provides the ability to make raw data meaningful and useful as information for decision-making purposes. The use of AI for decision making in IoT and data analytics will be crucial for efficient and effective decision making, especially in the area of streaming data and real-time analytics associated with edge computing networks.

Story continues

Real-time data will be a key value proposition for all use cases, segments, and solutions. The ability to capture streaming data, determine valuable attributes, and make decisions in real-time will add an entirely new dimension to service logic. In many cases, the data itself, and actionable information will be the service.

Report Benefits:

Forecasts for AI in big data analytics 2021 to 2026

Identify the highest potential AI technology area opportunities

Understand AI strategies and initiatives of leading companies

Learn the optimal use of AI for smart predictive analytics in IoT data

Understand the AI in Big Data, Analytics, and IoT ecosystem and value chain

Identify opportunities for AI in Analytics for IoT and other unstructured data

Select Report Findings:

Global market for AI in big data and IoT as a whole will reach $27.3B by 2026

Embedded AI in support of IoT-connected things will reach $6.3B globally by 2026

AI makes IoT data 27% more efficient and analytics 48% more effective for industry apps

Overall market for AI in big data and IoT will be led by Asia Pac followed by North America

AI in industrial machines will reach $727M globally by 2026 with collaborative robot growth at 42.5% CAGR

AI in autonomous weapon systems will reach $203M globally by 2026 with AI in military robotics growing at 40.3% CAGR

Machine learning will become a key AI technology to realize the full potential of big data and IoT, particularly in edge computing platforms

Top three segments will be: (1) Data Mining and Automation, (2) Automated Planning, Monitoring, and Scheduling, and (3) Data Storage and Customer Intelligence

Key Topics Covered:

1.0 Executive Summary

2.0 Introduction

3.0 Overview

Artificial Intelligence and Machine Learning

AI Types

AI & ML Language

Artificial Intelligence Technology

AI and ML Technology Goal

AI Approaches

AI Tools

AI Outcomes

Neural Network and Artificial Intelligence

Deep Learning and Artificial Intelligence

Predictive Analytics and Artificial Intelligence

Internet of Things and Big Data Analytics

IoT and Artificial Intelligence

Consumer IoT, Big Data Analytics, and Artificial Intelligence

Industrial IoT, Big Data Analytics, and Machine Learning

Artificial intelligence and cognitive computing

Transhumanism or H+ and Artificial Intelligence

Rise of Analysis of Things (AoT)

Supervised vs. Unsupervised Learning

AI as New form of UI

4.0 AI Technology in Big Data and IoT

Machine Learning Everywhere

Machine Learning APIs and Big Data Development

Phases of Machine Learning APIs

Machine Learning API Challenges

Top Machine Learning APIs

IBM Watson API

Microsoft Azure Machine Learning API

Google Prediction API

Amazon Machine Learning API

BigML

AT&T Speech API

Wit.ai

AlchemyAPI

Diffbot

PredictionIO

4.0 Machine Learning API in the General Application Environment

Enterprise Benefits of Machine Learning

Machine Learning in IoT Data

Ultra Scale Analytics and Artificial Intelligence

Rise of Algorithmic Business

Cloud Hosted Machine Intelligence

Contradiction of Machine Learning

Value Chain Analysis

5.0 AI Technology Application and Use Case

Intelligence Performance Monitoring

Infrastructure Monitoring

Generating Accurate Models

Recommendation Engine

Blockchain and Crypto Technologies

Enterprise Application

Contextual Awareness

Customer Feedback

Self-Driving Car

Fraud Detection System

Personalized Medicine and Healthcare Service

Predictive Data Modelling

Smart Machines

Cybersecurity Solutions

Autonomous Agents

Intelligent Assistant

Intelligent Decision Support System

Risk Management

Data Mining and Management

Intelligent Robotics

Financial Technology

Machine Intelligence

6.0 AI Technology Impact on Vertical Market

Enterprise Productivity Gain

Digital Twinning and Physical Asset Security

IT Process Efficiency Increase

AI to Replace Human Form Work

The rest is here:
Global Artificial Intelligence in Big Data Analytics and IoT Report 2021: Data Capture, Information and Decision Support Services Markets 2021-2026 -...