Big Data in the Automotive Industry: 2018 – 2030 – Opportunities, Challenges, Strategies & Forecasts

Release Date: July 2018

Number of Pages: 501

Number of Tables and Figures: 99

Synopsis: “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.

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.

Sample Request:

For a Sample and Table of Contents please contact info@snstelecom.com

Pricing:

The report is available for the following price:

  • Single User License: USD 2,500
  • Company Wide License: USD 3,500

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.

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 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
  • 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?

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