Big Data in the Automotive Market Poised to Grow More than $2.8 Billion USD at CAGR of more than 12% by 2030

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"Big Data in the Automotive Industry: 2017-2030-Opportunities, Challenges, Strategies and Forecasts" provides Strategic recommendations for Big Data vendors, automotive OEMs and other stakeholders

“Big Data” originally emerged as a term to describe datasets whose size is beyond the ability of traditional databases to capture, store, manage and analyze. However, the scope of the term has significantly expanded over the years. Big Data not only refers to the data itself but also a set of technologies that capture, store, manage and analyze large and variable collections of data, to solve complex problems.

List of Companies Mentioned

1010data, Absolutdata, Accenture, ACEA (European Automobile Manufacturers’ Association), Actian Corporation, Adaptive Insights, Advizor Solutions, AeroSpike, AFS Technologies, Alation, Algorithmia, Alibaba, Alliance of Automobile Manufacturers, Alluxio Alphabet, Alpine Data, Alteryx, AMD (Advanced Micro Devices), Apixio, Arcadia Data, Arimo, ARM, ASF (Apache Software Foundation), AtScale, Attivio, Attunity, Audi, Automated Insights, automotiveMastermind, AWS (Amazon Web Services), Axiomatics, Ayasdi, Basho Technologies, BCG (Boston Consulting Group), Bedrock Data, BetterWorks, Big Cloud Analytics, Big Panda, BigML, Birst, Bitam, Blue Medora, BlueData Software, BlueTalon, BMC Software, BMW, BOARD International, Booz Allen Hamilton, Boxever, CACI International, Cambridge Semantics, Capgemini, Cazena, Centrifuge Systems, etc....

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Amid the proliferation of real-time and historical data from sources such as connected devices, web, social media, sensors, log files and transactional applications, Big Data is rapidly gaining traction from a diverse range of vertical sectors. The automotive industry is no exception to this trend, where Big Data has found a host of applications ranging from product design and manufacturing to predictive vehicle maintenance and autonomous driving.

Big Data investments in the automotive industry will account for over $2.8 Billion in 2017 alone. Led by a plethora of business opportunities for automotive OEMs, tier-1 suppliers, insurers, dealerships and other stakeholders, these investments are further expected to grow at a CAGR of approximately 12% over the next three years.

The “Big Data in the Automotive Industry: 2017 – 2030 – Opportunities, Challenges, Strategies & Forecasts” report presents an in-depth assessment of Big Data in the automotive industry including key market drivers, challenges, investment potential, application areas, use cases, future roadmap, value chain, case studies, vendor profiles and strategies. The report also presents market size forecasts for Big Data hardware, software and professional services investments from 2017 through to 2030. The forecasts are segmented for 8 horizontal submarkets, 4 application areas, 18 use cases, 6 regions and 35 countries.
The report comes with an associated Excel datasheet suite covering quantitative data from all numeric forecasts presented in the report.

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Topics Covered

The report covers the following topics:
- Big Data ecosystem
- Market drivers and barriers
- Enabling technologies, standardization and regulatory initiatives
- Big Data analytics and implementation models
- Business case, key applications and use cases in the automotive industry
- 30 case studies of Big Data investments by automotive OEMs and other stakeholders
- Future roadmap and value chain
- Company profiles and strategies of over 240 Big Data vendors
- Strategic recommendations for Big Data vendors, automotive OEMs and other stakeholders
- Market analysis and forecasts from 2017 till 2030

Major Points From TOC:

Chapter 1: Introduction 22
Chapter 2: An Overview of Big Data 36
Chapter 3: Big Data Analytics 49
Chapter 4: Business Case & Applications in the Automotive Industry 57
Chapter 5: Automotive Industry Case Studies 70
Chapter 6: Future Roadmap & Value Chain 108
Chapter 7: Standardization & Regulatory Initiatives 114
Chapter 8: Market Analysis & Forecasts 134
Chapter 9: Vendor Landscape 181
Chapter 10: Conclusion & Strategic Recommendations 438

Forecast Segmentation

Market forecasts are provided for each of the following submarkets and their subcategories:
Hardware, Software & Professional Services
Horizontal Submarkets
Application Areas
Use Cases
Regional Markets
Country Markets

Key Findings

The report has the following key findings:
- In 2017, Big Data vendors will pocket over $2.8 Billion from hardware, software and professional services revenues in the automotive industry. These investments are further expected to grow at a CAGR of approximately 12% over the next three years, eventually accounting for over $4 Billion by the end of 2020.
- In a bid to improve customer retention, automotive OEMs are heavily relying on Big Data and analytics to integrate an array of data-driven aftermarket services such as predictive vehicle maintenance, real-time mapping and personalized concierge services.
- In recent years, several prominent partnerships and M&A deals have taken place that highlight the growing importance of Big Data in the automotive industry. For example, tier-1 supplier Delphi recently led an investment round to raise over $25 Million for Otonomo, a startup that has developed a data exchange and marketplace platform for vehicle-generated data.
- Addressing privacy concerns is necessary in order to monetize the swaths of Big Data that will be generated by a growing installed base of connected vehicles and other segments of the automotive industry.

Related Report:

The Big Data Market: 2017-2030-Opportunities, Challenges, Strategies, Industry Verticals and Forecasts : “Big Data” originally emerged as a term to describe datasets whose size is beyond the ability of traditional databases to capture, store, manage and analyze. However, the scope of the term has significantly expanded over the years.

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