Big Data in the Automotive Industry 2019
Description:-
Big Data is a word used to denote a massive volume of structured, semi-structured or unstructured data that is difficult to manage and process using traditional database and software tools.
Big Data has the potential to help organizations improve their internal operations and make intelligent decisions and strategies. This data is extracted from varying sources including organizational databases, emails, mobile devices, applications, servers, and customer queries and feedbacks. This massive data, when captured, formatted, manipulated, stored, maintained, and then analyzed, can support an organization to attain useful insight to improved revenues, get or retain clients and improve business operations.
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While the word may seem to refer to the volume of data, that isn’t always the scenario. The word big data, particularly when used by vendor or tool providers, may refer to the technology (which includes the tools and procedures) that the companies require to handle the massive amounts of data and storage structures.
Amid the accumulation of real-time and historical data from different sources such as web, log files, social media, connected devices, sensors, and transactional applications, Big Data is gaining traction from a distinct range of vertical sectors such as insurance industries, healthcare organizations and so on. The automotive industry is no exception to this trend, where Big Data is capable to offer a host of applications ranging from component and product design and manufacturing to autonomous driving and predictive vehicle maintenance.
Reports given by Researcher suppose that Big Data and analytics investments in the automotive industry was more than $3.3 Billion in the year 2018. Led by plenty of business development opportunities for automotive OEMs, insurers, tier-1 suppliers, dealers, and other stakeholders, these investments are further anticipated to grow at a CAGR of almost 16% over the coming three years.
With the help of Big Data technology, automotive OEMs and other key stakeholders have started using vehicle-generated data assets in a different innovative manner ranging from usage-based insurance and predictive vehicle maintenance to the personalized concierge, real-time mapping and autonomous driving.
Market segmentation-
The growth of the market can be forecasted based on the following segments:
Based on product type, the market can be further segmented into-
Software
Hardware
Professional services
Based on application areas, the market can be divided into-
Product Development, Manufacturing & Supply Chain
Connected Vehicles & Intelligent Transportation
Marketing, Sales & Other Applications
After-Sales, Warranty & Dealer Management
The important use-cases of employing Big Data technology in the automotive industry-
Supply Chain Management
Product Design, Planning, and manufacturing
Predictive product Maintenance & Real-Time Diagnostics
Component inventory and Pricing Optimization
Recall and Warranty Management
Dealer Management & Customer care Services
Usage-based insurance
Autonomous & Semi-Autonomous Driving
Intelligent Transportation
Driver Safety & Vehicle Cyber Security
In-Vehicle Experience, Navigation & Infotainment
Others
Region-based segmentation-
Asia Pacific, Eastern Europe, Latin & Central America, Middle East & Africa, North America, and Western Europe are the important regions that contribute to the growth and development of this market.
Facts
Data analytics technology can be employed to design & manufacture automobiles. Designing blunders are sometimes very costly once they progress from sketch level to manufacturing and production unit. With the implementation of big data analytics in the design & planning software, manufacturers can search for flaws while the automobile is still in the blueprint state. This saves a lot of cost and time spent on designing.
Analytics technology can track alterations in design, quality of the work, the entire production procedures as well as the safety of the vehicle & its parts. This can also cut down the substantial cost associated with designing, manufacturing & warehouse management.
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