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Big Data in the Automotive Industry, 2018-2021 Report - Market Forecast to Reach $5 Billion

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Big Data in the Automotive Industry, 2018-2021 Report - Market Forecast to Reach $5 Billion

PR Newswire

DUBLIN, Sept. 3, 2018 /PRNewswire/ --

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The "Big Data in the Automotive Industry: 2018 - 2030 - Opportunities, Challenges, Strategies & Forecasts" report from SNS Telecom & IT has been added to ResearchAndMarkets.com's offering.

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.

This research 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.

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.

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.

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.

Key Topics Covered:

Chapter 1: Introduction

  • Executive Summary
  • Topics Covered
  • Forecast Segmentation
  • Key Questions Answered
  • Key Findings
  • Methodology
  • Target Audience
  • Companies & Organizations Mentioned

Chapter 2: An Overview of Big Data

  • What is Big Data?
  • Key Approaches to Big Data Processing
  • Hadoop
  • NoSQL
  • MPAD (Massively Parallel Analytic Databases)
  • In-Memory Processing
  • Stream Processing Technologies
  • Spark
  • Other Databases & Analytic Technologies
  • Key Characteristics of Big Data
  • Volume
  • Velocity
  • Variety
  • Value
  • Market Growth Drivers
  • Awareness of Benefits
  • Maturation of Big Data Platforms
  • Continued Investments by Web Giants, Governments & Enterprises
  • Growth of Data Volume, Velocity & Variety
  • Vendor Commitments & Partnerships
  • Technology Trends Lowering Entry Barriers
  • Market Barriers
  • Lack of Analytic Specialists
  • Uncertain Big Data Strategies
  • Organizational Resistance to Big Data Adoption
  • Technical Challenges: Scalability & Maintenance
  • Security & Privacy Concerns

Chapter 3: Big Data Analytics

  • What are Big Data Analytics?
  • The Importance of Analytics
  • Reactive vs. Proactive Analytics
  • Customer vs. Operational Analytics
  • Technology & Implementation Approaches
  • Grid Computing
  • In-Database Processing
  • In-Memory Analytics
  • Machine Learning & Data Mining
  • Predictive Analytics
  • NLP (Natural Language Processing)
  • Text Analytics
  • Visual Analytics
  • Graph Analytics
  • Social Media, IT & Telco Network Analytics

Chapter 4: Business Case & Applications in the Automotive Industry

  • Overview & Investment Potential
  • Industry Specific Market Growth Drivers
  • Industry Specific Market Barriers
  • Key Applications
  • Product Development, Manufacturing & Supply Chain
  • Optimizing the Supply Chain
  • Eliminating Manufacturing Defects
  • Customer-Driven Product Design & Planning
  • After-Sales, Warranty & Dealer Management
  • Predictive Maintenance & Real-Time Diagnostics
  • Streamlining Recalls & Warranty
  • Parts Inventory & Pricing Optimization
  • Dealer Management & Customer Support Services
  • Connected Vehicles & Intelligent Transportation
  • 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 & Other Applications
  • Marketing & Sales
  • Customer Retention
  • Third Party Monetization
  • Other Applications

Chapter 5: Automotive Industry Case Studies

  • Automotive OEMs
  • Audi: Facilitating Efficient Production Processes with Big Data
  • BMW: Eliminating Defects in New Vehicle Models with Big Data
  • Daimler: Ensuring Quality Assurance with Big Data
  • Dongfeng Motor Corporation: Enriching Network-Connected Autonomous Vehicles with Big Data
  • FCA (Fiat Chrysler Automobiles): Enhancing Dealer Management with Big Data
  • Ford Motor Company: Making Efficient Transportation Decisions with Big Data
  • GM (General Motors Company): Personalizing In-Vehicle Experience with Big Data
  • Groupe PSA: Reducing Industrial Energy Bills with Big Data
  • Groupe Renault: Boosting Driver Safety with Big Data
  • Honda Motor Company: Improving F1 Performance & Fuel Efficiency with Big Data
  • Hyundai Motor Company: Empowering Connected & Self-Driving Cars with Big Data
  • Jaguar Land Rover: Realizing Better & Cheaper Vehicle Designs with Big Data
  • Mazda Motor Corporation: Creating Better Engines with Big Data
  • Nissan Motor Company: Leveraging Big Data to Drive After-Sales Business Growth
  • SAIC Motor Corporation: Transforming Stressful Driving to Enjoyable Moments with Big Data
  • Subaru: Turbocharging Dealer Interaction with Big Data
  • Suzuki Motor Corporation: Accelerating Vehicle Design and Innovation with Big Data
  • Tesla: Achieving Customer Loyalty with Big Data
  • Toyota Motor Corporation: Powering Smart Cars with Big Data
  • Volkswagen Group: Transitioning to End-to-End Mobility Solutions with Big Data
  • Volvo Cars: Reducing Breakdowns and Failures with Big Data
  • Other Stakeholders
  • Allstate Corporation & Arity: Making Transportation Safer & Smarter with Big Data
  • automotiveMastermind: Helping Automotive Dealerships Increase Sales with Big Data
  • Continental: Making Vehicles Safer with Big Data
  • Cox Automotive: Transforming the Used Vehicle Lifecycle with Big Data
  • Dash Labs: Turning Regular Cars into Data-Driven Smart Cars with Big Data
  • Delphi Automotive: Monetizing Connected Vehicles with Big Data
  • Denso Corporation: Enabling Hazard Prediction with Big Data
  • HERE: Easing Traffic Congestion with Big Data
  • Lytx: Ensuring Road Safety with Big Data
  • Michelin: Optimizing Tire Manufacturing with Big Data
  • Progressive Corporation: Rewarding Safe Drivers & Improving Traffic Safety with Big Data
  • Bosch: Empowering Fleet Management & Vehicle Insurance with Big Data
  • THTA (Tokyo Hire-Taxi Association): Making Connected Taxis a Reality with Big Data
  • Uber Technologies: Revolutionizing Ride Sourcing with Big Data
  • U.S. Xpress: Driving Fuel-Savings with Big Data

Chapter 6: Future Roadmap & Value Chain

  • Future Roadmap
  • Pre-2020: Investments in Advanced Analytics for Vehicle-Related Services
  • 2020 - 2025: Proliferation of Real-Time Edge Analytics & Automotive Data Monetization
  • 2025 - 2030: Towards Fully Autonomous Driving & Future IoT Applications
  • The Big Data Value Chain
  • Hardware Providers
  • Storage & Compute Infrastructure Providers
  • Networking Infrastructure Providers
  • Software Providers
  • Hadoop & Infrastructure Software Providers
  • SQL & NoSQL Providers
  • Analytic Platform & Application Software Providers
  • Cloud Platform Providers
  • Professional Services Providers
  • End-to-End Solution Providers
  • Automotive Industry

Chapter 7: Standardization & Regulatory Initiatives

  • ASF (Apache Software Foundation)
  • Management of Hadoop
  • Big Data Projects Beyond Hadoop
  • CSA (Cloud Security Alliance)
  • BDWG (Big Data Working Group)
  • CSCC (Cloud Standards Customer Council)
  • Big Data Working Group
  • DMG (Data Mining Group)
  • PMML (Predictive Model Markup Language) Working Group
  • PFA (Portable Format for Analytics) Working Group
  • IEEE (Institute of Electrical and Electronics Engineers)
  • Big Data Initiative
  • INCITS (InterNational Committee for Information Technology Standards)
  • Big Data Technical Committee
  • ISO (International Organization for Standardization)
  • ISO/IEC JTC 1/SC 32: Data Management and Interchange
  • ISO/IEC JTC 1/SC 38: Cloud Computing and Distributed Platforms
  • ISO/IEC JTC 1/SC 27: IT Security Techniques
  • ISO/IEC JTC 1/WG 9: Big Data
  • Collaborations with Other ISO Work Groups
  • ITU (International Telecommunication Union)
  • ITU-T Y.3600: Big Data - Cloud Computing Based Requirements and Capabilities
  • Other Deliverables Through SG (Study Group) 13 on Future Networks
  • Other Relevant Work
  • Linux Foundation
  • ODPi (Open Ecosystem of Big Data)
  • NIST (National Institute of Standards and Technology)
  • NBD-PWG (NIST Big Data Public Working Group)
  • OASIS (Organization for the Advancement of Structured Information Standards)
  • Technical Committees
  • ODaF (Open Data Foundation)
  • Big Data Accessibility
  • ODCA (Open Data Center Alliance)
  • Work on Big Data
  • OGC (Open Geospatial Consortium)
  • Big Data DWG (Domain Working Group)
  • TM Forum
  • Big Data Analytics Strategic Program
  • TPC (Transaction Processing Performance Council)
  • TPC-BDWG (TPC Big Data Working Group)
  • W3C (World Wide Web Consortium)
  • Big Data Community Group
  • Open Government Community Group

Chapter 8: Market Sizing & Forecasts

  • Global Outlook for Big Data in the Automotive Industry
  • Hardware, Software & Professional Services Segmentation
  • Horizontal Submarket Segmentation
  • Hardware Submarkets
  • Storage and Compute Infrastructure
  • Networking Infrastructure
  • Software Submarkets
  • Hadoop & Infrastructure Software
  • SQL
  • NoSQL
  • Analytic Platforms & Applications
  • Cloud Platforms
  • Professional Services Submarket
  • Professional Services
  • Application Area Segmentation
  • Product Development, Manufacturing & Supply Chain
  • After-Sales, Warranty & Dealer Management
  • Connected Vehicles & Intelligent Transportation
  • Marketing, Sales & Other Applications
  • Use Case Segmentation
  • Product Development, Manufacturing & Supply Chain Use Cases
  • Supply Chain Management
  • Manufacturing
  • Product Design & Planning
  • After-Sales, Warranty & Dealer Management Use Cases
  • Predictive Maintenance & Real-Time Diagnostics
  • Recall & Warranty Management
  • Parts Inventory & Pricing Optimization
  • Dealer Management & Customer Support Services
  • Connected Vehicles & Intelligent Transportation Use Cases
  • 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 & Other Application Use Cases
  • Marketing & Sales
  • Customer Retention
  • Third Party Monetization
  • Other Use Cases

Chapter 9: Vendor Landscape

  • 1010data
  • Absolutdata
  • Accenture
  • Actian Corporation/HCL Technologies
  • Adaptive Insights
  • Adobe Systems
  • Advizor Solutions
  • AeroSpike
  • AFS Technologies
  • Alation
  • Algorithmia
  • Alluxio
  • ALTEN
  • Alteryx
  • AMD (Advanced Micro Devices)
  • Anaconda
  • Apixio
  • Arcadia Data
  • ARM
  • AtScale
  • Attivio
  • Attunity
  • Automated Insights
  • AVORA
  • AWS (Amazon Web Services)
  • Axiomatics
  • Ayasdi
  • BackOffice Associates
  • Basho Technologies
  • BCG (Boston Consulting Group)
  • Bedrock Data
  • BetterWorks
  • Big Panda
  • BigML
  • Bitam
  • Blue Medora
  • BlueData Software
  • BlueTalon
  • BMC Software
  • BOARD International
  • Booz Allen Hamilton
  • Boxever
  • CACI International
  • Cambridge Semantics
  • Capgemini
  • Cazena
  • Centrifuge Systems
  • CenturyLink
  • Chartio
  • Cisco Systems
  • Civis Analytics
  • ClearStory Data
  • Cloudability
  • Cloudera
  • Cloudian
  • Clustrix
  • CognitiveScale
  • Collibra
  • Concurrent Technology/Vecima Networks
  • Confluent
  • Contexti
  • Couchbase
  • Crate.io
  • Cray
  • Databricks
  • Dataiku
  • Datalytyx
  • Datameer
  • DataRobot
  • DataStax
  • Datawatch Corporation
  • DDN (DataDirect Networks)
  • Decisyon
  • Dell Technologies
  • Deloitte
  • Demandbase
  • Denodo Technologies
  • Dianomic Systems
  • Digital Reasoning Systems
  • Dimensional Insight
  • Dolphin Enterprise Solutions Corporation/Hanse Orga Group
  • Domino Data Lab
  • Domo
  • Dremio
  • DriveScale
  • Druva
  • Dundas Data Visualization
  • DXC Technology
  • Elastic
  • Engineering Group (Engineering Ingegneria Informatica)
  • EnterpriseDB Corporation
  • eQ Technologic
  • Ericsson
  • Erwin
  • EVO (Big Cloud Analytics)
  • EXASOL
  • EXL (ExlService Holdings)
  • Facebook
  • FICO (Fair Isaac Corporation)
  • Figure Eight
  • FogHorn Systems
  • Fractal Analytics
  • Franz
  • Fujitsu
  • Fuzzy Logix
  • Gainsight
  • GE (General Electric)
  • Glassbeam
  • GoodData Corporation
  • Google/Alphabet
  • Grakn Labs
  • Greenwave Systems
  • GridGain Systems
  • H2O.ai
  • HarperDB
  • Hedvig
  • Hitachi Vantara
  • Hortonworks
  • HPE (Hewlett Packard Enterprise)
  • Huawei
  • HVR
  • HyperScience
  • HyTrust
  • IBM Corporation
  • iDashboards
  • IDERA
  • Ignite Technologies
  • Imanis Data
  • Impetus Technologies
  • Incorta
  • InetSoft Technology Corporation
  • InfluxData
  • Infogix
  • Infor/Birst
  • Informatica
  • Information Builders
  • Infosys
  • Infoworks
  • Insightsoftware.com
  • InsightSquared
  • Intel Corporation
  • Interana
  • InterSystems Corporation
  • Jedox
  • Jethro
  • Jinfonet Software
  • Juniper Networks
  • KALEAO
  • Keen IO
  • Keyrus
  • Kinetica
  • KNIME
  • Kognitio
  • Kyvos Insights
  • LeanXcale
  • Lexalytics
  • Lexmark International
  • Lightbend
  • Logi Analytics
  • Logical Clocks
  • Longview Solutions/Tidemark
  • Looker Data Sciences
  • LucidWorks
  • Luminoso Technologies
  • Maana
  • Manthan Software Services
  • MapD Technologies
  • MapR Technologies
  • MariaDB Corporation
  • MarkLogic Corporation
  • Mathworks
  • Melissa
  • MemSQL
  • Metric Insights
  • Microsoft Corporation
  • MicroStrategy
  • Minitab
  • MongoDB
  • Mu Sigma
  • NEC Corporation
  • Neo4j
  • NetApp
  • Nimbix
  • Nokia
  • NTT Data Corporation
  • Numerify
  • NuoDB
  • NVIDIA Corporation
  • Objectivity
  • Oblong Industries
  • OpenText Corporation
  • Opera Solutions
  • Optimal Plus
  • Oracle Corporation
  • Palantir Technologies
  • Panasonic Corporation/Arimo
  • Panorama Software
  • Paxata
  • Pepperdata
  • Phocas Software
  • Pivotal Software
  • Prognoz
  • Progress Software Corporation
  • Provalis Research
  • Pure Storage
  • PwC (PricewaterhouseCoopers International)
  • Pyramid Analytics
  • Qlik
  • Qrama/Tengu
  • Quantum Corporation
  • Qubole
  • Rackspace
  • Radius Intelligence
  • RapidMiner
  • Recorded Future
  • Red Hat
  • Redis Labs
  • RedPoint Global
  • Reltio
  • RStudio
  • Rubrik/Datos IO
  • Ryft
  • Sailthru
  • Salesforce.com
  • Salient Management Company
  • Samsung Group
  • SAP
  • SAS Institute
  • ScaleOut Software
  • Seagate Technology
  • Sinequa
  • SiSense
  • Sizmek
  • SnapLogic
  • Snowflake Computing
  • Software AG
  • Splice Machine
  • Splunk
  • Strategy Companion Corporation
  • Stratio
  • Streamlio
  • StreamSets
  • Striim
  • Sumo Logic
  • Supermicro (Super Micro Computer)
  • Syncsort
  • SynerScope
  • SYNTASA
  • Tableau Software
  • Talend
  • Tamr
  • TARGIT
  • TCS (Tata Consultancy Services)
  • Teradata Corporation
  • Thales/Guavus
  • ThoughtSpot
  • TIBCO Software
  • Toshiba Corporation
  • Transwarp
  • Trifacta
  • Unifi Software
  • Unravel Data
  • VANTIQ
  • VMware
  • VoltDB
  • WANdisco
  • Waterline Data
  • Western Digital Corporation
  • WhereScape
  • WiPro
  • Wolfram Research
  • Workday
  • Xplenty
  • Yellowfin BI
  • Yseop
  • Zendesk
  • Zoomdata
  • Zucchetti

Chapter 10: Conclusion & Strategic Recommendations

  • Why is the Market Poised to Grow?
  • Geographic Outlook: Which Countries Offer the Highest Growth Potential?
  • Partnerships & M&A Activity: Highlighting the Importance of Big Data
  • The Significance of Edge Analytics for Automotive Applications
  • Achieving Customer Retention with Data-Driven Services
  • Addressing Privacy Concerns
  • The Role of Legislation
  • Encouraging Data Sharing in the Automotive Industry
  • Assessing the Impact of Self-Driving Vehicles
  • Recommendations
  • Big Data Hardware, Software & Professional Services Providers
  • Automotive OEMS & Other Stakeholders

For more information about this report visit https://www.researchandmarkets.com/research/wj5jh9/big_data_in_the?w=5

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