Product Code: MB1A-01-00-00-00
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
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.
Key Questions This Study Will Answer
- How does the Big Data and Analytics market compare across different sectors? What impact does it have on the manufacturing sector? What are the four functional blocks of a holistic Big Data and Analytics solution offering?
- What additional infrastructure is required for manufacturing end users to leverage vital Big Data? What are the key parameters they need to take into account to select the right deployment model? What are the benefits of adoption?
- How can analytics be applied across business segments in a manufacturing facility? In which area are manufacturing end users expected to witness the greatest value? How do individual personnel prefer to visualize their data? What are some of the new roles and responsibilities required?
- What is the market size for maintenance analytics? Why are companies transitioning from reactive to proactive analytics? How does Big Data aid in facilitating lean manufacturing? What are some of the emerging applications for Big Data that are still underpenetrated?
- Why are NoSQL and Hadoop critical for any future Big Data project? What is the size of the opportunity? Why do distributed assets require a machine-to-machine application development platform? What is the size of the opportunity?
- What are some of the key trends across geographical regions? Which among process or discrete manufacturing is likely to witness greater acceptance for Big Data and Analytics? What are some of the key vertical markets expected to experience higher growth? What are some of the emerging markets?
Table of Contents
1. EXECUTIVE SUMMARY
2. INTERNET OF INDUSTRIAL THINGS-A RESEARCH PERSPECTIVE
- 1. Internet of Industrial Things-The Four Functional Facets
- 2. Frost & Sullivan's Offering
3. RESEARCH SCOPE AND OBJECTIVES
- 1. Research Scope and Objective
- 2. Key Questions This Study Will Answer
4. EXAMINING THE FUNCTIONAL COMPONENTS OF A BIG DATA SOLUTION AND UNEARTHING ITS POTENTIAL FOR
- 1. Business Case for the Implementation of a Big Data Solution
- 2. Snapshot of Manufacturing vs. Other Sectors
- 3. Building Blocks of a Big Data Solution for Manufacturing
- 4. Data Storage and Integration-Analyzing the Foundation Layers
- 5. On-Premise vs. Cloud Based-Choosing the Right Deployment Model
- 6. Cloud-based Models-Acute Focus on Data Sensitivity
- 7. Hadoop and NoSQL Databases-Extension to Existing Infrastructure
- 8. Manufacturing Analytics-A Gold Mine of Opportunities
- 9. Risk Reward Matrices-Production Line and Plant Level
- 10. Evolution of Data Analytics for Maintenance-related Activities
- 11. Analytics for the Extended Value Chain-Supply Chain Optimization
- 12. Data Visualization-Customized Dashboards for Individual Personnel
- 13. Data Driven Workforce-Dissolving Barriers Across the Enterprise
5. SEIZING LUCRATIVE BIG DATA OPPORTUNITIES TO GAIN A FIRST-MOVER ADVANTAGE-"ATM" FRAMEWORK
- 1. Opportunity Mapping Using the ATM Framework
- 2. Maintenance Analytics-Increased Equipment Uptime and Performance
- 3. Era of Advanced Machine Learning-A Proactive Approach
- 4. Curtailing the 7 Wastes in Manufacturing to Form a Lean Enterprise
- 5. Push Towards Energy Optimization
- 6. Influx of Unstructured Data to Stir Demand for NoSQL Databases
- 7. Majority of Big Data Projects are Expected to be Built on Hadoop
- 8. M2M Application Development Platforms
- 9. Regional Outlook-Key Dynamics Across Global Hotspots
- 10. Vertical Market Analysis-Discrete vs. Process Manufacturing
- 11. New Emerging Markets-Manufacturing Pollution Control
- 12. Size of the Pie-Summary of Key Market Opportunities
6. MARKET DIRECTION-INNOVATIVE COMPANIES DEVELOPING VALUE-ADDED PRODUCTS, SOLUTIONS, AND SERVICES
- 1. Company 1-Mtell
- 2. Company 2-ThingWorx (a PTC Company)
- 3. Company 3-Sisense Inc.
- 4. Company 4-MongoDB Inc.
- 5. Company 5-Hortonworks Inc.
- 6. Legal Disclaimer
7. THE FROST & SULLIVAN STORY
- 1. The Frost & Sullivan Story
- 2. Value Proposition: Future of Your Company & Career
- 3. Industry Convergence
- 4. Global Perspective
- 5. 360° Research Perspective
- 6. Implementation Excellence
- 7. Our Blue Ocean Strategy