Big Data in the Automotive Industry – Opportunities, Challenges, Strategies & Forecasts 2017 –
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.
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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.
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 &
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
Manufacturing
Product Design & Planning
Predictive Maintenance &
Recall & Warranty Management
Parts Inventory & Pricing Optimization
Dealer Management &
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
Latin &
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Country Markets
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 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
The report has the following key findings:
In 2017, Big Data vendors will pocket over
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
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.
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List of Companies Mentioned
1010data
Absolutdata
Accenture
ACEA (
Alation
Algorithmia
Alibaba
Alluxio
Alphabet
Alpine Data
AMD (Advanced Micro Devices)
Arcadia Data
Arimo
ARM
ASF (
AtScale
Attivio
Audi
Automated Insights
automotiveMastermind
AWS (
Axiomatics
BCG (
Big Cloud Analytics
Big
BigML
Birst
Bitam
Blue Medora
Boxever
Cambridge Semantics
Centrifuge Systems
Chartio
ClearStory Data
CognitiveScale
Confluent
Contexti
Continental
Continuum Analytics
CSA (
CSCC (
DataScience
Datos IO
DDN (DataDirect Networks)
Dell
Deloitte
Dimensional Insight
DMG (
Domo
DriveScale
Dundas Data Visualization
Eligotech
Engineering Group (
eQ Technologic
EXASOL
Facebook
FICO (
Fujitsu
Fuzzy Logix
Geely (
Glassbeam
Google
Greenwave Systems
Groupe PSA
H2O.ai
HDS (
HERE
HPE (
Huawei
iDashboards
IEC (
IEEE (
Impetus Technologies
INCITS (
Incorta
Infer
Infoworks
ISO (
Jaguar Land Rover
Jedox
Jethro
KALEAO
Keen IO
Kinetica
KNIME
Kyvos Insights
Lavastorm
Lexus
Luminoso Technologies
Lytx
Magento Commerce
MapD Technologies
Mathworks
Mercedes-Benz
METI (
Metric Insights
Michelin
Minitab
Mu Sigma
Neo Technology
NetApp
Nimbix
NIST (
OASIS (
ODaF (
ODCA (
ODPi (Open Ecosystem of Big Data)
OGC (
Opera Solutions
Optimal Plus
Otonomo
Prognoz
PwC (
Pyramid Analytics
Qlik
Rackspace
Radius Intelligence
RapidMiner
RedPoint Global
Rosenberger
RStudio
Ryft Systems
SAP
ScaleDB
Snowflake Computing
Splice Machine
Splunk
Sqrrl
Striim
Sumo Logic
Supermicro (
Syncsort
SynerScope
Talena
Tamr
TARGIT
TCS (
Tesla
The Floow
THTA (
Tidemark
TPC (
Unravel Data
Valens
Waterline Data
WiPro
Workday
Xevo
Yseop
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