“Big Data in the Automotive Industry

Big Data in the Automotive Industry Market 2017-2030 – Company Profiles and Strategies of Over 240 Big Data Vendors -Research and Markets



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.

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 author estimates that 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 report comes with an associated Excel datasheet suite covering quantitative data from all numeric forecasts presented in the report.

Key Questions Answered

– 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 2020 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

– 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.

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

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

Companies Mentioned

– 1010data
– ACEA (European Automobile Manufacturers’ Association)
– AFS Technologies
– AMD (Advanced Micro Devices)
– ARM
– ASF (Apache Software Foundation)
– AWS (Amazon Web Services)
– Absolutdata
– Accenture
– Actian Corporation
– Adaptive Insights
– Advizor Solutions
– AeroSpike
– Alation
– Algorithmia
– Alibaba
– Alliance of Automobile Manufacturers
– Alluxio
– Alphabet
– Alpine Data
– Alteryx
– Apixio
– Arcadia Data
– Arimo
– AtScale
– Attivio
– Attunity
– Audi
– Automated Insights
– automotiveMastermind
– Axiomatics
– Ayasdi
– BCG (Boston Consulting Group)
– BMC Software
– BMW
– BOARD International
– Basho Technologies
– Bedrock Data
– BetterWorks
– Big Cloud Analytics
– Big Panda
– BigML
– Birst
– Bitam
– Blue Medora
– BlueData Software
– BlueTalon
Booz Allen Hamilton
– Boxever
– CACI International
– CSA (Cloud Security Alliance)
– CSCC (Cloud Standards Customer Council)
– Cambridge Semantics
– Capgemini
– Cazena
– Centrifuge Systems
– CenturyLink
– Chartio
– Cisco Systems
– Civis Analytics
– ClearStory Data
– Cloudability
– Cloudera
– Clustrix
– CognitiveScale
– Collibra
– Concurrent Computer Corporation
– Confluent
– Contexti
– Continental
– Continuum Analytics
– Couchbase
– CrowdFlower
– DDN (DataDirect Networks)
– DMG  (Data Mining Group)
– DXC Technology
– Daimler
– Dash Labs
– DataGravity
– DataRobot
– DataScience
– DataStax
– DataTorrent
– Databricks
– Dataiku
– Datameer
– Datawatch Corporation
– Datos IO
– Decisyon
– Dell EMC
– Dell Technologies
– Deloitte
– Delphi Automotive
– Demandbase
– Denodo Technologies
– Denso Corporation
– Digital Reasoning Systems
– Dimensional Insight
– Dolphin Enterprise Solutions Corporation
– Domino Data Lab
– Domo
– DriveScale
– Dundas Data Visualization
– EXASOL
– Eligotech
– Engie
– Engineering Group (Engineering Ingegneria Informatica)
– EnterpriseDB
– eQ Technologic
– Ericsson
– FCA (Fiat Chrysler Automobiles)
– FICO (Fair Isaac Corporation)
– FTC (U.S. Federal Trade Commission)
– Facebook
– Ford Motor Company
– Fractal Analytics
– Fujitsu
– Fuzzy Logix
– GE (General Electric)
– GM (General Motors Company)
– Gainsight
– Geely (Zhejiang Geely Holding Group)
– Glassbeam
– GoodData Corporation
– Google
– Greenwave Systems
– GridGain Systems
– Groupe PSA
– Groupe Renault
– Guavus
– H2O.ai
– HDS (Hitachi Data Systems)
– HERE
– HPE (Hewlett Packard Enterprise)
– Hedvig
– Honda Motor Company
– Hortonworks
– Huawei
– Hyundai Motor Company
– IBM Corporation
– iDashboards
– IEC (International Electrotechnical Commission)
– IEEE (Institute of Electrical and Electronics Engineers)
– INCITS (InterNational Committee for Information Technology Standards)
– ISO (International Organization for Standardization)
– Impetus Technologies
– Incorta
– InetSoft Technology Corporation
– Infer
– Infor
– Informatica Corporation
– Information Builders
– Infosys
– Infoworks
– InsightSquared
– Insightsoftware.com
– Intel Corporation
– InterSystems Corporation
– Interana
– Jaguar Land Rover
– Jedox
– Jethro
– Jinfonet Software
– Juniper Networks
– KALEAO
– KDDI Corporation
– KNIME
– Keen IO
– Kia Motor Corporation
– Kinetica
– Kognitio
– Kyvos Insights
– Lavastorm
– Lexalytics
– Lexmark International
– Lexus
– Linux Foundation
– Logi Analytics
– Longview Solutions
– Looker Data Sciences
– LucidWorks
– Luminoso Technologies
– Lytx
– METI (Ministry of Economy, Trade and Industry, Japan)
– Maana
– Magento Commerce
– Manthan Software Services
– MapD Technologies
– MapR Technologies
– MariaDB Corporation
– MarkLogic Corporation
– Mathworks
– Mazda Motor Corporation
– MemSQL
– Mercedes-Benz
– Metric Insights
– Michelin
– MicroStrategy
– Microsoft Corporation
– Minitab
– MongoDB
– Mu Sigma
– NEC Corporation
– NIST (U.S. National Institute of Standards and Technology)
– NTT Data Corporation
– NTT Group
– NVIDIA Corporation
– NYC DOT (New York City Department of Transportation)
– Neo Technology
– NetApp
– Nimbix
– Nissan Motor Company
– Nokia
– Numerify
– NuoDB
– Nutonian
– OASIS (Organization for the Advancement of Structured Information Standards)
– ODCA (Open Data Center Alliance)
– ODPi (Open Ecosystem of Big Data)
– ODaF (Open Data Foundation)
– OGC (Open Geospatial Consortium)
– Oblong Industries
– OpenText Corporation
– Opera Solutions
– Optimal Plus
– Oracle Corporation
– Otonomo
– Palantir Technologies
– Panorama Software
– Paxata
– Pentaho Corporation
– Pepperdata
– Phocas Software
– Pivotal Software
– Prognoz
– Progress Software Corporation
– PwC (PricewaterhouseCoopers International)
– Pyramid Analytics
– Qlik
– Quantum Corporation
– Qubole
– RStudio
– Rackspace
– Radius Intelligence
– RapidMiner
– Recorded Future
– Red Hat
– RedPoint Global
Redis Labs
– Reltio
Robert Bosch
– Rocket Fuel
– Rosenberger
– Ryft Systems
– SAIC Motor Corporation
– SAP
– SAS Institute
– SCIO Health Analytics
– Sailthru
– Salesforce.com
– Salient Management Company
– Samsung Group
– ScaleDB
– ScaleOut Software
– Seagate Technology
– SiSense
– Sinequa
– SnapLogic
– Snowflake Computing
– Software AG
– Splice Machine
– Splunk
– Sqrrl
– Strategy Companion Corporation
– StreamSets
– Striim
– Subaru
– Sumo Logic
– Supermicro (Super Micro Computer)
– Suzuki Motor Corporation
– Syncsort
– SynerScope
– TARGIT
– TCS (Tata Consultancy Services)
– THTA (Tokyo Hire-Taxi Association)
– TIBCO Software
– TM Forum
– TPC (Transaction Processing Performance Council)
– Tableau Software
– Talena
– Talend
– Tamr
– Teradata Corporation
– Tesla
– The Floow
– ThoughtSpot
– Tidemark
– Toshiba Corporation
– Toyota Motor Corporation
– Trifacta
– Uber Technologies
– Unravel Data
– VMware
– Valens
– Volkswagen Group
– VoltDB
– Volvo Cars
– W3C (World Wide Web Consortium)
– Waterline Data
– Western Digital Corporation
– WiPro
– Workday
– Xevo
– Xplenty
– Yellowfin International
– Yseop
– Zendesk
– Zoomdata
– Zucchetti

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