Global Data Analytics for Industries Report, 2017–2023

Rise of Progressive Analytic Techniques Expected to Induce New Business Models in Manufacturing

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Analytics have been around for a long time in different forms. Starting with manual data collection, it has progressed to reporting systems and then to statistical-based modelling systems. The progressive improvement in computer prowess simultaneously backed by electronic advancement in sensor technology has led to an era of convergence. This has created innumerable data points and allows technology to make sense of it. Businesses are racing to convert raw machine and process data into actionable and useful insights in real-time. While predictive analytics allows problem identification before its occurrence, prescriptive analytics educates the user on the best solution after taking into the process constraints

Table of Contents

1. Executive Summary
Key Findings
2. Industrial Internet of Things—A Research Perspective
IIoT—Emerging Themes in the Industrial Environment
IIoT—Key Attributes of a Smart Factory
Frost & Sullivan’s Value Proposition in IIoT
3. Research Scope and Objectives
4. Overview of Big Data and Advanced Analytics
Data Analytics for Process and Discrete Manufacturing
The Paradigm Shift Towards Being Predictive
The Five Strategic Shifts of Industrie 4.0
Lifecycle Mapping and Key Workforce Requirements
5. The Know-How of Advanced Analytics
On-Time with Analytics—Public Transport Train Systems
Manufacturing with Analytics—Polymer Plant
Discerning Customer Needs
Manufacturing Leaning Towards Analytics
Prescribing the Next Move with Analytics
Progressing Business Scenarios
Movers and Shakers—TrendMiner
Movers and Shakers—RiverLogic
The Boom of Big Data Analytics
6. Growth Opportunities and Call to Action
Transformation in the Big Data and Analytics Market
Growth Opportunity 1—Data Socialisation
Growth Opportunity 2—Self Healing Machines
Growth Opportunity 3—Analytics in Augmented Reality
Growth Opportunity 4—Virtual Plant
Big Bets of the Future—Key Growth Prospects
Strategic Imperatives for Advanced Analytics Market
7. The Last Word
3 Big Predictions
Legal Disclaimer
8. Appendix
Market Engineering Methodology


List of Figures & Charts

1. Data Analytics for Industries: Key Findings, Global, 2016
2. Data Analytics for Industries: Key Questions this Study will Answer, Global, 2016
3. Data Analytics for Industries: Key Questions this Section will Answer, Global, 2016
4. Data Analytics for Industries: Data Analytics for Process and Discrete Manufacturing, Global, 2016
5. Data Analytics for Industries: The Paradigm Shift Towards Being Predictive, Global, 2016
6. Data Analytics for Industries: The Five Strategic Shifts of Industrie 4.0, Global, 2016
7. Data Analytics for Industries: Lifecycle Mapping and Key Workforce Requirements, Global, 2016
8. Data Analytics for Industries: Key Questions this Section will Answer, Global, 2016
9. Data Analytics for Industries: On-Time with Analytics—Public Transport Train Systems, Global, 2016
10. Data Analytics for Industries: Manufacturing with Analytics—Polymer Plant, Global, 2016
11. Data Analytics for Industries: Discerning Customer Needs, Global, 2016
12. Data Analytics for Industries: Manufacturing Leaning Towards Analytics, Global, 2016
13. Data Analytics for Industries: Prescribing the Next Move with Analytics, Global, 2016
14. Data Analytics for Industries: Progressing Business Scenarios, Global, 2016
15. Data Analytics for Industries: Company Profile TrendMiner, Global, 2016
16. Data Analytics for Industries: Company Profile—RiverLogic, Global, 2016
17. Data Analytics for Industries: The Boom of Big Data Analytics, Global, 2016
18. Data Analytics for Industries: Key Questions this Section will Answer, Global, 2016
19. Data Analytics for Industries: Transformation in the Big Data and Analytics Market, Global, 2016
20. Data Analytics for Industries: Big Bets of the Future—Key Growth Prospects, Global, 2016
21. Data Analytics for Industries: Strategic Imperatives for Advanced Analytics Market, Global, 2016



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