Future of Big Data Analytics, Related Business Models, and Automotive Use Cases, Forecast to 2025

Data Ownership and Monetization Channels will Accelerate Big Data Analytics Growth to $10.54 Billion by 2025

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The automotive Big Data analytics ecosystem will be a confluence of several related sectors from sensor manufacturers, wearable's companies to telecommunications providers in addition to traditional ecosystem. This research provides an in-depth analysis of the Big Data analytics initiatives across the automotive digitalization pillars. OEMs and Tier Is will continue to invest in Big Data analytics companies during 2017 to 2020. Partnerships and collaboration are critical for data monetization.

The future roadmap of digitalization in the automotive industry is expected to move rapidly from “digital services” to “car-as-a-service” to “mobility-as-a-service”, transforming the car into an element of a connected living solution by 2030. In the year 2016, digitalization underpins the transformation of business activities, process improvements, and the development of new competencies and business models across five key pillars within the automotive industry—Connected Supply Chain, Industrial Internet of Things and Industry 4.0, Connected and Autonomous Cars, Digital Retailing, and Mobility as a Service (MaaS).

The study analyzes the strategies, growth analysis, competitive landscape, business models, and future focus areas of original equipment manufacturers (OEMs), technology companies, startups, and Tier I suppliers. Digitalization in the automotive industry will have a spiral effect on other industries. OEMs and Tier Is realized that digitization along with IoT, technology partnerships, software capabilities, and customized solutions will be the way forward for the global automotive industry from the year 2016 to 2025.

OEMs digitalization strategy will rely heavily on data analytics and it must include vehicle digitalization, organization digitalization, customer focused strategies, and future mobility concepts in addition to targeting new business models. New investments from OEMs will be leveraged for innovations and transformations in 2017. Automotive OEMs and Tier Is will execute agile IT projects and leverage digital and BDA expertise from new startups.

In addition to OEMs and Tier I suppliers initiatives, this study covers a detailed list of startups and technology companies across the five key pillars.

Key Questions this Study will Answer:

Why is Big Data important in the era of automotive digital transformation and where it can help in terms of features and services?
What are the key markets for startups to venture into and what is the current revenue potential of those markets?
What is the current level of involvement of key global OEMs and what are the available opportunities?
Considering automotive digitalization, how much will the automotive industry spend from technology and software perspective?
What are the revenue opportunities and business models in automotive digitalization and Big Data analytics?

Table of Contents

1. Executive Summary—Introduction to Big Data Analytics in the Automotive Industry
Key Findings
OEM and Tier I Highlights
Automotive Big Data Analytics—Use Cases and Focus Areas
Overview of Automotive IT Spending—2016–2025
Automotive Big Data Analytics Ecosystem
Autonomous Service Packages—Monetize with Analytics
Automotive Industry—Disruptive Technologies and Companies
Data Monetization—Direct and Indirect Revenue Opportunities
2. Research Scope, Objectives, Methodology, and Background
Research Scope and Objectives
Research Background
Vehicle Segment Definitions
Frost & Sullivan—CES 2017 Interviews
Research Methodology
3. Automotive Big Data Analytics Market—Digitalization Trends and Data Driven Use Cases
Big Data Analytics Impact on Automotive Digitalization Pillars
Big Data and Technology Partnerships to Drive Self Driving Cars
Self Learning Revenue Opportunities
ADAS Roadmap—ACC, PA, and FCW
ADAS Roadmap—BSD, FCW, and NV
Vehicles Embedded with Sensors—Advanced Biometrics
Biometrics in Passenger Vehicles—Forecast
OEM and Tier I—Gamification Initiatives to Improve BDA Potential
Automotive Gamification—Key Driver for Big Data Analytics
Emerging Business Models in Aftermarket eRetailing
Usage Based Insurance—Focus towards Data-driven Future
Disruptive Business Model in UBI—Vision Based Driver Scoring-Nexar
4. Automotive IT Spending and Big Data Analytics—Market Analysis
Overview of Automotive IT Spending—2016–2025
Overview of Automotive IT Spending in Key Areas—2016–2025
Automotive Big Data Analytics Spending—2016–2025
5. Automotive Big Data Analytics—OEM Activities, Data Points, Use Cases, and Case Studies
Automotive OEMs—Recent Big Data Analytics Initiatives
Automotive OEMs—IoT Platforms
Ford Invests in AI and Machine Learning Companies
Ford Partnership with Pivotal
General Motors (GM)—Digital Transformation Elements
GM Cloud Based IoT Analytics to Reduce Factory Downtime
BMW Supply Chain Optimization with Teradata
Volkswagen Data Lab Competencies
Volkswagen Digital Lab and Enhanced Digital Platform
Ford, GM, and Toyota—Data Points and Use Cases
Tesla, BMW, Mercedes Benz, and Hyundai—Data Points and Use Cases
Nissan, Honda, and Audi—Data Points and Use Cases
6. Automotive Big Data Analytics—Tier I Supplier Profiles
Bosch Software Innovations (SI)—Key Highlights and Partnerships
Bosch SI—Leading User and Solution Provider
Bosch and Tom Tom—Radar Road Signature
Delphi Acquisition of Control-Tec and Movimento
Delphi Automotive Software Suite
Delphi Offering Holistic Connected Vehicle Platform
Goodyear Powers Concept Tire with AI for Autonomous Vehicles
HERE Focus on Automated Driving and Connected Services
ZF Friedrichshafen AG
7. Automotive Big Data Analytics—Technology Companies and Startup Profiles
D-Wave Systems Inc.
Preferred Networks, Inc. (PFN)
Preferred Networks, Inc. (PFN) Deep Learning Analytics
Pivotal Software, Inc
Pivotal Software, Inc—Automotive OEM Engagements
Nexar
Badgeville
Bunchball
Zendrive
8. Automotive Big Data Analytics—Growth Opportunity Analysis
Growth Opportunity—Disruptive Technologies and Business Models
Automotive Digital Transformation and BDA—Strategic Imperatives
Automotive Digitalization—BDA Companies
Data Analytics—Future of Automotive Aftermarket
BDA Convergence with Artificial Intelligence (AI) Ecosystem
9. Key Conclusions and Future Outlook
Digitalization Recommendations to Automotive OEMs
The Last Word—Three Big Predictions
Legal Disclaimer
10. Appendix—Digital Transformation Framework
Table of Acronyms Used
Product
Operations
People
Information Management
Customer Journey
Leadership
Market Engineering Methodology

Infographic



List of Figures & Charts

1. Automotive Big Data Analytics Market: Key Findings, Global, 2016–2030
2. Automotive Big Data Analytics Market: Vehicle Segment Definitions, Global, 2016
3. Automotive Big Data Analytics Market: Key Participants, Global, 2016
4. Automotive Big Data Analytics Market: Advanced Biometrics, Global, 2016–2025
5. Automotive Big Data Analytics Market: OEM Big Data Analytics Initiatives, Global, 2016 and 2017
6. Automotive Big Data Analytics Market: Ford Investments, Global, 2016 and 2017
7. Automotive Big Data Analytics Market: OEM Data Points and Use Cases, Global, 2016–2020
8. Automotive Big Data Analytics Market: OEM Data Points and Use Cases, Global, 2016–2020
9. Automotive Big Data Analytics Market: OEM Data Points and Use Cases, Global, 2016–2020
10. Automotive Big Data Analytics Market: Pivotal Software—OEM Engagements, Global, 2017


1. Automotive Big Data Analytics Market: OEM Highlights, Global, 2016–2020
2. Automotive Big Data Analytics Market: Focus Areas and Use Cases, Global, 2016?2025
3. Automotive Big Data Analytics Market: IT Spending, Global, 2016–2025
4. Automotive Big Data Analytics Market: Ecosystem, Global, 2016
5. Automotive Big Data Analytics Market: Autonomous Service Packages, Global, 2017
6. Automotive Big Data Analytics Market: Key Companies, Global, 2017
7. Automotive Big Data Analytics Market: Automotive Data Monetization, Global, 2017
8. Automotive Big Data Analytics Market: Research Background, Global, 2016
9. Automotive Big Data Analytics Market: Five Pillars of Digitalization, Global, 2016
10. Automotive Big Data Analytics Market: Self Driving Consortium, Global, 2017
11. Automotive Big Data Analytics Market: Self Driving Revenue Opportunities, Global, 2016–2025
12. Automotive Big Data Analytics Market: ADAS Roadmap, Global, 2016–2025
13. Automotive Big Data Analytics Market: Self Driving Revenue Opportunities, Global, 2016–2025
14. Automotive Big Data Analytics Market: Biometric Passenger Vehicles, Global, 2016–2025
15. Automotive Big Data Analytics Market: Gamification Initiatives, Global, 2016–2020
16. Automotive Big Data Analytics Market: Gamification Drivers, Global, 2016–2020
17. Automotive Big Data Analytics Market: Business Models in eRetailing, Global, 2016–2025
18. Automotive Big Data Analytics Market: IT Spending, Global, 2016–2025
19. Automotive Big Data Analytics Market: Automotive IT Spending by Key Areas, Global, 2016–2025
20. Automotive Big Data Analytics Market: Big Data Spending, Global, 2016–2025
21. Automotive Big Data Analytics Market: OEM IoT Platforms, Global, 2016
22. Automotive Big Data Analytics Market: GM Transformation Elements, Global, 2016
23. Automotive Big Data Analytics Market: GM Cloud Based IoT Analytics, Global, 2016
24. Automotive Big Data Analytics Market: BMW Engagement, Global, 2016
25. Automotive Big Data Market: Volkswagen Data Lab Competencies, Global, 2017
26. Automotive Big Data Analytics Market: Radar Road Signature, Global, 2017–2020
27. Automotive Big Data Analytics Market: Delphi Automotive Software Suite, Global, 2017
28. Automotive Big Data Analytics Market: Delphi Connected Vehicle Platform, Global, 2017
29. Automotive Big Data Analytics Market: Goodyear Power Concept Tire, Global, 2017
30. Automotive Big Data Analytics Market: HERE Focus on Automated Driving and Connected Services, Global, 2017
31. Automotive Big Data Analytics Market: ZF Friedrichshafen AG, Global, 2017
32. Automotive Big Data Analytics Market: D-Wave Systems Inc., Global, 2017
33. Automotive Big Data Analytics Market: Preferred Networks, Global, 2017
34. Automotive Big Data Analytics Market: Preferred Networks—DL Analytics, Global, 2017
35. Automotive Big Data Analytics Market: Pivotal Software, Global, 2017
36. Automotive Big Data Analytics Market: Nexar, Global, 2017
37. Automotive Big Data Analytics Market: Badgeville, Global, 2017
38. Automotive Big Data Analytics Market: Bunchball, Global, 2017
39. Automotive Big Data Analytics Market: Zendrive, Global, 2017
40. Automotive Big Data Market: Big Data Analytics Companies, Global, 2016–2025
41. Automotive Big Data Analytics Market: OEM Recommendations, Global, 2016–2022



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