Toggle Nav
My Cart
Search
Advanced Search
Menu
Account
Settings

Investing in the Currency of the Future: Big Data for the Manufacturing Domain

Investing in the Currency of the Future: Big Data for the Manufacturing Domain

Transition Towards Data-driven Real-time Visibility and Decision Making Compels Manufacturers to Adopt Big Data Solutions

RELEASE DATE
29-Jul-2015
REGION
Global
Research Code: MB1A-01-00-00-00
SKU: IA01239-GL-MR_16772
AvailableYesPDF Download
$5,000.00
In stock
SKU
IA01239-GL-MR_16772
$5,000.00
DownloadLink
Add to Compare
ENQUIRE NOW

Description

As part of the Internet of Industrial Things (IOIT) research portfolio offering from the Industrial Automation and Process Control practice, this strategic research service provides a detailed assessment of the key opportunities for Big Data and Analytics in the manufacturing domain from an application, technology, and market standpoint. While the deliverable encompasses a combination of both qualitative trends and quantitative data points, some of the key focal areas here include new storage requirements for high volume multiple data types , the role of analytics in manufacturing, emerging applications within the facility , new markets for sustainable growth, and innovative company initiatives that are gaining wide-scale acceptance.

RESEARCH: INFOGRAPHIC

This infographic presents a brief overview of the research, and highlights the key topics discussed in it.
Click image to view it in full size

Table of Contents

Key Findings

  • Technological Drivers
  • Market Drivers

Internet of Industrial Things—The 4 Functional Facets

Frost & Sullivan’s Offering

  • Investing in the Currency of the Future: Big Data for the Manufacturing Domain

Research Scope and Objective

Business Case for the Implementation of a Big Data Solution

Snapshot of Manufacturing vs. Other Sectors

Building Blocks of a Big Data Solution for Manufacturing

Data Storage and Integration—Analyzing the Foundation Layers

On-Premise vs. Cloud Based—Choosing the Right Deployment Model

Cloud-based Models—Acute Focus on Data Sensitivity

Hadoop and NoSQL Databases—Extension to Existing Infrastructure

Manufacturing Analytics—A Gold Mine of Opportunities

Risk Reward Matrices—Production Line and Plant Level

Evolution of Data Analytics for Maintenance-related Activities

Analytics for the Extended Value Chain—Supply Chain Optimization

Data Visualization—Customized Dashboards for Individual Personnel

Data Driven Workforce—Dissolving Barriers Across the Enterprise

Opportunity Mapping Using the ATM Framework

Maintenance Analytics—Increased Equipment Uptime and Performance

Era of Advanced Machine Learning—A Proactive Approach

Curtailing the 7 Wastes in Manufacturing to Form a Lean Enterprise

Push Towards Energy Optimization

Influx of Unstructured Data to Stir Demand for NoSQL Databases

Majority of Big Data Projects are Expected to be Built on Hadoop

M2M Application Development Platforms

Regional Outlook—Key Dynamics Across Global Hotspots

Vertical Market Analysis—Discrete vs. Process Manufacturing

New Emerging Markets—Manufacturing Pollution Control

Size of the Pie—Summary of Key Market Opportunities

Company 1—Mtell

Company 2—ThingWorx (a PTC Company)

Company 3—Sisense Inc.

Company 4—MongoDB Inc.

Company 5—Hortonworks Inc.

Legal Disclaimer

Value Proposition: Future of Your Company & Career

Global Perspective

Industry Convergence

360º Research Perspective

Implementation Excellence

Our Blue Ocean Strategy

List of Figures
  • 1. Big Data for the Manufacturing Domain: Key Findings, Global, 2014
  • 2. Big Data for the Manufacturing Domain: Research Scope and Objective, Global, 2014
  • 3. Big Data for the Manufacturing Domain: Business Case for the Implementation of a Big Data Solution, Global, 2014–2021
  • 4. Big Data for the Manufacturing Domain: Snapshot of Manufacturing vs. Other Sectors, Global, 2014–2021
  • 5. Big Data for the Manufacturing Domain: Building Blocks of a Big Data Solution for Manufacturing Operations, Global, 2014
  • 6. Big Data for the Manufacturing Domain: Data Storage and Integration—Analyzing the Foundation Layers, Global, 2014
  • 7. Big Data for the Manufacturing Domain: On-premise vs. Cloud Based–Choosing the Right Deployment Model, Global, 2014
  • 8. Big Data for the Manufacturing Domain: Cloud-based Models–Acute Focus on Data Sensitivity, Global, 2014
  • 9. Big Data for the Manufacturing Domain: Hadoop and NoSQL Databases—Extension to Existing Infrastructure , Global, 2014
  • 10. Big Data for the Manufacturing Domain: Manufacturing Analytics–A Gold Mine of Opportunities, Global, 2014–2021
  • 11. Big Data for the Manufacturing Domain: Risk Reward Matrices–Production Line and Plant Level, Global, 2014–2021
  • 12. Big Data for the Manufacturing Domain: Analytics for the Extended Value Chain—Supply Chain Optimization, Global, 2014
  • 13. Big Data for the Manufacturing Domain: Data Visualization—Customized Dashboards for Individual Personnel, Global, 2014
  • 14. Big Data for the Manufacturing Domain: Data Driven Workforce—Dissolving Barriers Across the Enterprise, Global, 2014–2021
  • 15. Big Data for the Manufacturing Domain: Opportunity Mapping using the ?ATM? (Application, Technology, Markets) Framework, Global, 2014–2021
  • 16. Big Data for the Manufacturing Domain: Revenue Forecast, Global, 2014–2021
  • 17. Big Data for the Manufacturing Domain: Comparison between Diagnostic and Prescriptive Analytical Platforms—Market Metrics, Global, 2014–2021
  • 18. Big Data for the Manufacturing Domain: Enabling a Lean Enterprise Using Big Data, Global, 2014
  • 19. Big Data for the Manufacturing Domain: M2M Application Development Platforms (MAP), Global, 2014–2021
  • 20. Big Data for the Manufacturing Domain: Regional Outlook, Global, 2014–2021
  • 21. Big Data for the Manufacturing Domain: Vertical Market Analysis, Global, 2014–2021
  • 22. Big Data for the Manufacturing Domain: ThingWorx, Global, 2014
  • 23. Big Data for the Manufacturing Domain: Sisense Inc. , Global, 2014
  • 24. Big Data for the Manufacturing Domain: MongoDB Inc., Global, 2014
  • 25. Big Data for the Manufacturing Domain: Hortonworks Inc., Global, 2014
List of Charts
  • 1. Big Data for the Manufacturing Domain: Evolution of Data Analytics for Maintenance-related Activities, Global, 2000–2020
  • 2. Big Data for the Manufacturing Domain: Energy Consumption, Global, 2014–2021
  • 3. Big Data for the Manufacturing Domain: Energy Management Platform, Global, 2014–2021
  • 4. Big Data for the Manufacturing Domain: SQLvs. NoSQL, Global, 2014–2021
  • 5. Big Data for the Manufacturing Domain: Hadoop Market Overview, Global, 2014–2021
  • 6. Big Data for the Manufacturing Domain: Waste Disposal and Treatment Costs, Global, 2014
  • 7. Big Data for the Manufacturing Domain: Size of the Pie–Summary of Key Market Opportunities, Global, 2014–2021
  • 8. Big Data for the Manufacturing Domain: Mtell, Global, 2014
Request Sample
Popular Topics

smart wearables market

mobile biometrics market

plastic recycling market

Top 10 Growth Opportunities for 2023

natural gas market

solar energy market

wearable technology market

nutritional supplement market

agrochemicals market

offshore market

As part of the Internet of Industrial Things (IOIT) research portfolio offering from the Industrial Automation and Process Control practice, this strategic research service provides a detailed assessment of the key opportunities for Big Data and Analytics in the manufacturing domain from an application, technology, and market standpoint. While the deliverable encompasses a combination of both qualitative trends and quantitative data points, some of the key focal areas here include new storage requirements for high volume multiple data types , the role of analytics in manufacturing, emerging applications within the facility , new markets for sustainable growth, and innovative company initiatives that are gaining wide-scale acceptance.
More Information
No Index No
Podcast No
Table of Contents | Executive Summary~ || Key Findings~ ||| Technological Drivers~ ||| Market Drivers~ | Internet of Industrial Things—A Research Perspective~ || Internet of Industrial Things—The 4 Functional Facets~ || Frost & Sullivan’s Offering~ ||| Investing in the Currency of the Future: Big Data for the Manufacturing Domain~ || Research Scope and Objective~ | Examining the Functional Components of a Big Data Solution and Unearthing its Potential for Manufacturing~ || Business Case for the Implementation of a Big Data Solution~ || Snapshot of Manufacturing vs. Other Sectors~ || Building Blocks of a Big Data Solution for Manufacturing~ || Data Storage and Integration—Analyzing the Foundation Layers~ || On-Premise vs. Cloud Based—Choosing the Right Deployment Model~ || Cloud-based Models—Acute Focus on Data Sensitivity~ || Hadoop and NoSQL Databases—Extension to Existing Infrastructure~ || Manufacturing Analytics—A Gold Mine of Opportunities~ || Risk Reward Matrices—Production Line and Plant Level~ || Evolution of Data Analytics for Maintenance-related Activities~ || Analytics for the Extended Value Chain—Supply Chain Optimization~ || Data Visualization—Customized Dashboards for Individual Personnel~ || Data Driven Workforce—Dissolving Barriers Across the Enterprise~ | Seizing Lucrative Big Data Opportunities to Gain a First-Mover Advantage—?ATM? Framework~ || Opportunity Mapping Using the ATM Framework~ || Maintenance Analytics—Increased Equipment Uptime and Performance~ || Era of Advanced Machine Learning—A Proactive Approach~ || Curtailing the 7 Wastes in Manufacturing to Form a Lean Enterprise~ || Push Towards Energy Optimization~ || Influx of Unstructured Data to Stir Demand for NoSQL Databases~ || Majority of Big Data Projects are Expected to be Built on Hadoop~ || M2M Application Development Platforms~ || Regional Outlook—Key Dynamics Across Global Hotspots~ || Vertical Market Analysis—Discrete vs. Process Manufacturing~ || New Emerging Markets—Manufacturing Pollution Control~ || Size of the Pie—Summary of Key Market Opportunities~ | Market Direction—Innovative Companies Developing Value-added Products, Solutions, and Services~ || Company 1—Mtell~ || Company 2—ThingWorx (a PTC Company)~ || Company 3—Sisense Inc.~ || Company 4—MongoDB Inc.~ || Company 5—Hortonworks Inc.~ || Legal Disclaimer~ | The Frost & Sullivan Story~ || Value Proposition: Future of Your Company & Career~ || Global Perspective~ || Industry Convergence~ || 360º Research Perspective~ || Implementation Excellence~ || Our Blue Ocean Strategy~
List of Charts and Figures 1. Big Data for the Manufacturing Domain: Key Findings, Global, 2014~ 2. Big Data for the Manufacturing Domain: Research Scope and Objective, Global, 2014~ 3. Big Data for the Manufacturing Domain: Business Case for the Implementation of a Big Data Solution, Global, 2014–2021~ 4. Big Data for the Manufacturing Domain: Snapshot of Manufacturing vs. Other Sectors, Global, 2014–2021~ 5. Big Data for the Manufacturing Domain: Building Blocks of a Big Data Solution for Manufacturing Operations, Global, 2014~ 6. Big Data for the Manufacturing Domain: Data Storage and Integration—Analyzing the Foundation Layers, Global, 2014~ 7. Big Data for the Manufacturing Domain: On-premise vs. Cloud Based–Choosing the Right Deployment Model, Global, 2014~ 8. Big Data for the Manufacturing Domain: Cloud-based Models–Acute Focus on Data Sensitivity, Global, 2014~ 9. Big Data for the Manufacturing Domain: Hadoop and NoSQL Databases—Extension to Existing Infrastructure , Global, 2014~ 10. Big Data for the Manufacturing Domain: Manufacturing Analytics–A Gold Mine of Opportunities, Global, 2014–2021~ 11. Big Data for the Manufacturing Domain: Risk Reward Matrices–Production Line and Plant Level, Global, 2014–2021~ 12. Big Data for the Manufacturing Domain: Analytics for the Extended Value Chain—Supply Chain Optimization, Global, 2014~ 13. Big Data for the Manufacturing Domain: Data Visualization—Customized Dashboards for Individual Personnel, Global, 2014~ 14. Big Data for the Manufacturing Domain: Data Driven Workforce—Dissolving Barriers Across the Enterprise, Global, 2014–2021~ 15. Big Data for the Manufacturing Domain: Opportunity Mapping using the ?ATM? (Application, Technology, Markets) Framework, Global, 2014–2021~ 16. Big Data for the Manufacturing Domain: Revenue Forecast, Global, 2014–2021~ 17. Big Data for the Manufacturing Domain: Comparison between Diagnostic and Prescriptive Analytical Platforms—Market Metrics, Global, 2014–2021~ 18. Big Data for the Manufacturing Domain: Enabling a Lean Enterprise Using Big Data, Global, 2014~ 19. Big Data for the Manufacturing Domain: M2M Application Development Platforms (MAP), Global, 2014–2021~ 20. Big Data for the Manufacturing Domain: Regional Outlook, Global, 2014–2021~ 21. Big Data for the Manufacturing Domain: Vertical Market Analysis, Global, 2014–2021~ 22. Big Data for the Manufacturing Domain: ThingWorx, Global, 2014~ 23. Big Data for the Manufacturing Domain: Sisense Inc. , Global, 2014~ 24. Big Data for the Manufacturing Domain: MongoDB Inc., Global, 2014~ 25. Big Data for the Manufacturing Domain: Hortonworks Inc., Global, 2014~| 1. Big Data for the Manufacturing Domain: Evolution of Data Analytics for Maintenance-related Activities, Global, 2000–2020~ 2. Big Data for the Manufacturing Domain: Energy Consumption, Global, 2014–2021~ 3. Big Data for the Manufacturing Domain: Energy Management Platform, Global, 2014–2021~ 4. Big Data for the Manufacturing Domain: SQLvs. NoSQL, Global, 2014–2021~ 5. Big Data for the Manufacturing Domain: Hadoop Market Overview, Global, 2014–2021~ 6. Big Data for the Manufacturing Domain: Waste Disposal and Treatment Costs, Global, 2014~ 7. Big Data for the Manufacturing Domain: Size of the Pie–Summary of Key Market Opportunities, Global, 2014–2021~ 8. Big Data for the Manufacturing Domain: Mtell, Global, 2014~
Author Rahul Vijayaraghavan
Industries Industrial Automation
WIP Number MB1A-01-00-00-00
Is Prebook No