Study of the Key Automotive Cloud Platforms & Applications in 2019 - Featuring Numerous Case Studies Including VW Automotive Cloud, Audi's AV Development, and More

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Mar 13, 2020, 12:30 ET

DUBLIN, March 13, 2020 /PRNewswire/ -- The "Global Automotive Data Management and Cloud Platform Strategies, 2019" report has been added to ResearchAndMarkets.com's offering.

The aim of this research study is to give an overview of automotive cloud platforms and the key cloud applications adopted in the automotive market. The study focuses on the different cloud platform strategies adopted by original equipment manufacturers (OEMs), key business models used, key cloud vendors, and their core features.

The publisher believes that automotive cloud and data management platforms will form the backbone of digitization initiatives in the industry. However, OEMs are challenged with technical skills in-house and, hence, are dependent on technology partnerships for building automotive cloud platforms.

Automakers understand the importance of managing data and deriving value from them. Cloud platforms are critical to move, store, secure, and index massive volumes of data generated from connected vehicles. However, only purpose-built cloud platforms exist today. Connected services deployment has one and smart manufacturing service has another. Data from connected and autonomous vehicles are collected and processed separately.

This situation gives rise to data scalability issues and accommodation of evolving technological changes. Therefore, automakers are seeking technological partners who will not just provide cloud solutions, but have the capabilities to build a unified data management platform with Artificial Intelligence (AI)/Machine Learning (ML) capabilities.

OEMs store connected data on private cloud, fearing security and privacy issues; this will be an expensive option in the long run. Hybrid cloud architecture will be the future for mass automakers. Less critical services will be on the public cloud and the sensitive use cases (such as OEM-specific vehicle testing and development) will be mostly on private cloud.

The hybrid cloud approach will be ideal once OEMs build the capabilities that are required to segment the critical datasets from non-critical ones. The publisher believes that 80-85% of the OEMs will transition to hybrid cloud architecture, owing to scale and cost benefits.

Automotive companies should lay down aggressive roadmaps for the development of futuristic data management strategies - including what level of data needs to be collected, how data labeling will happen, and what the level of scaling in future will be - and accordingly set up an ecosystem for storage, processing, and service delivery.

Cognitive capabilities should not be used for any specific application, but should be embedded throughout the cloud platforms. Automotive firms can, thereby, leverage deeper insights from generated data and create compelling use cases for connected and autonomous vehicles.

Key Topics Covered

1. Executive Summary

Key Findings
Key Trends Transforming the Autonomous and Connected Landscape
Growth in Connected Vehicles and Data
Different Layers of Automotive IoT Platform - Overview
Data Management Strategies Adopted in the Market
OEM - Technology Partnerships for Cloud
OEMs With In-house Strategies
VW Future Strategy - In-house Software Development
Automotive Cloud Platform - Future Opportunities
Automotive Cloud - Key Vendor Highlights
Automotive Cloud and Data Management - Current Vs. Future Outlook

2. Research Scope, Objectives, and Background

Research Scope
Key Questions this Study will Answer
Research Background

3. OEM Cloud Platform - Market Trends

Different Layers of Automotive IoT Platform - Overview
Global Automotive IoT Ecosystem - Participants
Key Applications of Automotive Cloud
OEM Approach Towards Cloud and Data Management
OEM Analysis - Connectivity and Cloud Partnerships
OEM Cloud Platform Analysis
Automotive Cloud - Key Vendor Highlights
Service Delivery Partners - Key Vendor Highlights
Future Opportunities for Automotive Cloud Platform

4. Connected Services

Global Connected Cars Forecast
Connected Services Through Cloud
Rise in Connected Vehicle Services
OEM Data Management Strategies - Connected Services
Deployment Model Analysis for Connected Services
Case Study: BMW Connected Services Architecture
Case Study: VW Automotive Cloud
Case Study: Daimler's eXtollo Cloud Platform

5. Autonomous Vehicles - Testing and Development

Market Volume of Automated Vehicles (L3/4) by 2030
AV Development Through Cloud
Autonomous Driving Services of the Future
OEM Data Management Strategies - AV Development
Automotive Cloud Platforms used for AV Development
Case Study: Toyota Research Institute and AWS IoT
Case Study: Audi's AV Development

6. Growth Opportunities and Companies to Action

Automotive Cloud Growth Opportunities
Strategic Imperatives for Success and Growth - Automotive Cloud Platform

7. The Last Word

3 Big Predictions

Companies Mentioned

Audi
BMW
Daimler
Toyota
VW

For more information about this report visit https://www.researchandmarkets.com/r/cznhtz

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