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.
The “Big Data in the Automotive Industry: 2018 to 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.
BIG DATA IN THE AUTOMOTIVE MARKET 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.
BIG DATA IN THE AUTOMOTIVE MARKET TOPICS COVERED:
Forecast Segmentation:
Market forecasts are provided for each of the following submarkets and their categories:
- 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
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Big Data in the Automotive Market 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
Big Data in the Automotive Market 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?
List of Companies Mentioned:
The following companies and organizations have been reviewed, discussed or mentioned in the report:
- 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
- AVORA
- AWS (Amazon Web Services)
- Axiomatics
- Ayasdi
- BackOffice Associates
- Basho Technologies
- BCG (Boston Consulting Group)
- Bedrock Data
- BetterWorks
- Big Panda
- BigML
- Birst
- Bitam
- Blue Medora
- BlueData Software
- BlueTalon
- BMC Software
- BMW
- BOARD International
- Booz Allen Hamilton
- Bosch
- Boxever
- CACI International
- Cambridge Semantics
- Capgemini
- Cazena
- Centrifuge Systems
- CenturyLink
- Chartio
- Cisco Systems
- Citroën
- Civis Analytics
- ClearStory Data
- Cloudability
- Cloudera
- Cloudian
- Clustrix
- CognitiveScale
- Collibra
- Concurrent Technology
- Confluent
- Contexti
- Continental
- Couchbase
- Cox Automotive
- Cox Enterprises
- Crate.io
- Cray
- CSA (Cloud Security Alliance)
- CSCC (Cloud Standards Customer Council)
- Daimler
- Dash Labs
- Databricks
- Dataiku
- Datalytyx
- Datameer
- DataRobot
- DataStax
- Datawatch Corporation
- Datos IO
- DDN (DataDirect Networks)
- Decisyon
- Dell Technologies
- Deloitte
- Delphi Automotive
- Demandbase
- Denodo Technologies
- Denso Corporation
- Dianomic Systems
- Digital Reasoning Systems
- Dimensional Insight
- DMG (Data Mining Group)
- Dolphin Enterprise Solutions Corporation
- Domino Data Lab
- Domo
- Dongfeng Motor Corporation
- Dremio
- DriveScale
- Druva
- DS Automobiles
- Ducati
- Dundas Data Visualization
- DXC Technology
- Elastic
- Engineering Group (Engineering Ingegneria Informatica)
- EnterpriseDB Corporation
- eQ Technologic
- Ericsson
- Erwin
- EVŌ (Big Cloud Analytics)
- EXASOL
- EXL (ExlService Holdings)
- Facebook
- FCA (Fiat Chrysler Automobiles)
- FICO (Fair Isaac Corporation)
- Figure Eight
- FogHorn Systems
- Ford Motor Company
- Fractal Analytics
- Franz
- Fujitsu
- Fuzzy Logix
- Gainsight
- GE (General Electric)
- Geely (Zhejiang Geely Holding Group)
- Glassbeam
- GM (General Motors Company)
- GoodData Corporation
- Google
- Grakn Labs
- Greenwave Systems
- GridGain Systems
- Groupe PSA
- Groupe Renault
- Guavus
- H2O.ai
- Hanse Orga Group
- HarperDB
- HCL Technologies
- Hedvig
- HERE
- Hitachi Vantara
- Honda Motor Company
- Hortonworks
- HPE (Hewlett Packard Enterprise)
- Huawei
- HVR
- HyperScience
- HyTrust
- Hyundai Motor Company
- IBM Corporation
- iDashboards
- IDERA
- IEC (International Electrotechnical Commission)
- IEEE (Institute of Electrical and Electronics Engineers)
- Ignite Technologies
- Imanis Data
- Impetus Technologies
- INCITS (InterNational Committee for Information Technology Standards)
- Incorta
- InetSoft Technology Corporation
- InfluxData
- Infogix
- Infor
- Informatica
- Information Builders
- Infosys
- Infoworks
- Insightsoftware.com
- InsightSquared
- Intel Corporation
- Interana
- InterSystems Corporation
- ISO (International Organization for Standardization)
- ITU (International Telecommunication Union)
- Jaguar Land Rover
- Jedox
- Jethro
- Jinfonet Software
- Juniper Networks
- KALEAO
- KDDI Corporation
- Keen IO
- Keyrus
- Kinetica
- KNIME
- Kognitio
- Kyvos Insights
- LeanXcale
- Lexalytics
- Lexmark International
- Lightbend
- Linux Foundation
- Logi Analytics
- Logical Clocks
- Longview Solutions
- Looker Data Sciences
- LucidWorks
- Luminoso Technologies
- Lytx
- Maana
- Manthan Software Services
- MapD Technologies
- MapR Technologies
- MariaDB Corporation
- MarkLogic Corporation
- Mathworks
- Mazda Motor Corporation
- Melissa
- MemSQL
- Mercedes-Benz
- METI (Ministry of Economy, Trade and Industry, Japan)
- Metric Insights
- Michelin
- Microsoft Corporation
- MicroStrategy
- Minitab
- Mobileye
- MongoDB
- Mu Sigma
- NEC Corporation
- Neo4j
- NetApp
- Nimbix
- Nissan Motor Company
- Nokia
- NTT Data Corporation
- NTT DoCoMo
- Numerify
- NuoDB
- NVIDIA Corporation
- OASIS (Organization for the Advancement of Structured Information Standards)
- Objectivity
- Oblong Industries
- ODaF (Open Data Foundation)
- ODCA (Open Data Center Alliance)
- OGC (Open Geospatial Consortium)
- OpenText Corporation
- Opera Solutions
- Optimal Plus
- Oracle Corporation
- Otonomo
- Palantir Technologies
- Panasonic Corporation
- Panorama Software
- Paxata
- Pepperdata
- Peugeot
- Phocas Software
- Pivotal Software
- Prognoz
- Progress Software Corporation
- Progressive 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
- Ryft
- SAIC Motor Corporation
- 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
- Subaru
- Sumo Logic
- Supermicro (Super Micro Computer)
- Suzuki Motor Corporation
- Syncsort
- SynerScope
- SYNTASA
- Tableau Software
- Talend
- Tamr
- TARGIT
- Tata Motors
- TCS (Tata Consultancy Services)
- Teradata Corporation
- Tesla
- Thales
- ThoughtSpot
- THTA (Tokyo Hire-Taxi Association)
- TIBCO Software
- Tidemark
- TM Forum
- Toshiba Corporation
- Toyota Motor Corporation
- TPC (Transaction Processing Performance Council)
- Transwarp
- Trifacta
- U.S. FTC (Federal Trade Commission)
- U.S. NIST (National Institute of Standards and Technology)
- U.S. Xpress
- Uber Technologies
- Unifi Software
- Unravel Data
- Valens
- VANTIQ
- Vecima Networks
- VMware
- Volkswagen Group
- VoltDB
- Volvo Cars
- W3C (World Wide Web Consortium)
- WANdisco
- Waterline Data
- Western Digital Corporation
- WhereScape
- WiPro
- Wolfram Research
- Workday
- Xevo
- Xplenty
- Yellowfin BI
- Yseop
- Zendesk
- Zoomdata
- Zucchetti