Thursday 28 February 2019

Research report explores the Big Data in the Automotive Market for the forecast period, 2019-2030

ResearchMoz presents professional and in-depth study of "Big Data in the Automotive Industry: 2018 - 2030 - Opportunities, Challenges, Strategies & 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. 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.

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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.

SNS Telecom & IT estimates that Big Data investments in the automotive industry will account for more than $3.3 Billion in 2018 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 16% over the next three years.

The “Big Data in the Automotive Industry: 2018 – 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 2018 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.

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, application areas and use cases in the automotive industry
     Over 35 case studies of Big Data investments by automotive OEMs and other stakeholders
     Future roadmap and value chain
     Profiles and strategies of over 270 leading and emerging Big Data ecosystem players
     Strategic recommendations for Big Data vendors, automotive OEMs and other stakeholders
     Market analysis and forecasts from 2018 till 2030

Forecast Segmentation

Market forecasts are provided for each of the following submarkets and their subcategories:

Hardware, Software & Professional Services

     Hardware
     Software
     Professional Services

Horizontal Submarkets

     Storage & Compute Infrastructure
     Networking Infrastructure
     Hadoop & Infrastructure Software
     SQL
     NoSQL
     Analytic Platforms & Applications
     Cloud Platforms
     Professional Services

Application Areas

     Product Development, Manufacturing & Supply Chain
     After-Sales, Warranty & Dealer Management
     Connected Vehicles & Intelligent Transportation
     Marketing, Sales & Other Applications

Use Cases

     Supply Chain Management
     Manufacturing
     Product Design & Planning
     Predictive Maintenance & Real-Time Diagnostics
     Recall & Warranty Management
     Parts Inventory & Pricing Optimization
     Dealer Management & Customer Support Services
     UBI (Usage-Based Insurance)
     Autonomous & Semi-Autonomous Driving
     Intelligent Transportation
     Fleet Management
     Driver Safety & Vehicle Cyber Security
     In-Vehicle Experience, Navigation & Infotainment
     Ride Sourcing, Sharing & Rentals
     Marketing & Sales
     Customer Retention
     Third Party Monetization
     Other Use Cases

Regional Markets

     Asia Pacific
     Eastern Europe
     Latin & Central America
     Middle East & Africa
     North America
     Western Europe

Country Markets

Argentina, Australia, Brazil, Canada, China, Czech Republic, Denmark, Finland, France, Germany,  India, Indonesia, Israel, Italy, Japan, Malaysia, Mexico, Netherlands, Norway, Pakistan, Philippines, Poland, Qatar, Russia, Saudi Arabia, Singapore, South Africa, South Korea, Spain, Sweden, Taiwan, Thailand, UAE, UK,  USA

Key Questions Answered

The report provides answers to the following key questions:

     How big is the Big Data opportunity in the automotive industry?
     How is the market evolving by segment and region?
     What will the market size be in 2021, and at what rate will it grow?
     What trends, challenges and barriers are influencing its growth?
     Who are the key Big Data software, hardware and services vendors, and what are their strategies?
     How much are automotive OEMs and other stakeholders investing in Big Data?
     What opportunities exist for Big Data analytics in the automotive industry?
     Which countries, application areas and use cases will see the highest percentage of Big Data investments in the automotive industry?

Key Findings

The report has the following key findings:

     In 2018, Big Data vendors will pocket more than $3.3 Billion from hardware, software and professional services revenues in the automotive industry. These investments are further expected to grow at a CAGR of approximately 16% over the next three years, eventually accounting for over $5 Billion by the end of 2021.
     Through the use of Big Data technologies, automotive OEMs and other stakeholders are beginning to exploit vehicle-generated data assets in a number of innovative ways ranging from predictive vehicle maintenance and UBI (Usage-Based Insurance) to real-time mapping, personalized concierge, autonomous driving and beyond.
     Edge analytics, which refers to the processing and analysis of information closer to the point of origin, is increasingly becoming an indispensable capability for applications such as autonomous driving where real-time data – from cameras, LiDAR and other on-board sensors – needs to be acted upon instantly and reliably.
     Privacy continues to remain a major concern, and ensuring the protection of sensitive information – through creative anonymization and dedicated cybersecurity investments  – 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.

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List of Companies Mentioned

    1010data
    Absolutdata
    Accenture
    ACEA (European Automobile Manufacturers’ Association)
    Actian Corporation
    Adaptive Insights
    Adobe Systems
    Advizor Solutions
    AeroSpike
    AFS Technologies
    Alation
    Algorithmia
    Allstate Corporation
    Alluxio
    Alphabet
    ALTEN
    Alteryx
    AMD (Advanced Micro Devices)
    Anaconda
    Apixio
    Arcadia Data
    Arimo
    Arity
    ARM
    ASF (Apache Software Foundation)
    AtScale
    Attivio
    Attunity
    Audi
    Automated Insights
    Automobili Lamborghini
    automotiveMastermind

Continue...

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