The Worldwide Big Data in the Automotive Market |Projected to Grow Healthy CAGR | Top Key Players - BMW , Daimler, FCA (Fiat Chrysler Automobiles), Ford Motor, GM (General Motors Company), Groupe PSA | Forecast till 2030

BusinessIndustryReports.com has new research report on the global Big Data in the Automotive Market. The global Big Data in the Automotive market is growing continuously and expected to grow healthy CAGR by Forecast year 2030

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.

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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 “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.

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Table of Contents

1 Chapter 1: Introduction

1.1 Executive Summary

1.2 Topics Covered

1.3 Forecast Segmentation

1.4 Key Questions Answered

1.5 Key Findings

1.6 Methodology

1.7 Target Audience

1.8 Companies & Organizations Mentioned

2 Chapter 2: An Overview of Big Data

2.1 What is Big Data?

2.2 Key Approaches to Big Data Processing

2.2.1 Hadoop

2.2.2 NoSQL

2.2.3 MPAD (Massively Parallel Analytic Databases)

2.2.4 In-Memory Processing

2.2.5 Stream Processing Technologies

2.2.6 Spark

2.2.7 Other Databases & Analytic Technologies

2.3 Key Characteristics of Big Data

2.3.1 Volume

2.3.2 Velocity

2.3.3 Variety

2.3.4 Value

2.4 Market Growth Drivers

2.4.1 Awareness of Benefits

2.4.2 Maturation of Big Data Platforms

2.4.3 Continued Investments by Web Giants, Governments & Enterprises

2.4.4 Growth of Data Volume, Velocity & Variety

2.4.5 Vendor Commitments & Partnerships

2.4.6 Technology Trends Lowering Entry Barriers

2.5 Market Barriers

2.5.1 Lack of Analytic Specialists

2.5.2 Uncertain Big Data Strategies

2.5.3 Organizational Resistance to Big Data Adoption

2.5.4 Technical Challenges: Scalability & Maintenance

2.5.5 Security & Privacy Concerns

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