With the advancement in technology, the internet’s function is increasing every day; a significant number of devices are connected to the internet. If we look back through time, fingerprint wearables, home electronics, and audio-visual devices have been introduced. Moreover, Automobile companies play a part in overtaking this market for their own use.
A new path of pursuit is created by incorporating Wi-Fi into automobiles that include vehicles connecting directly with the internet for GPS navigation, music streaming, and email. This service comprises Navigation, Infotainment, fleet management, automatic collision notification, remote diagnostics, improved safety, traffic management, usage-based insurance, and, finally, autonomous driving.
Data quality is the origin of the mentioned application in the automobile sector as it raises the volume of data obtained by remote sensors. This data is being analyzed and leveraged to transform the automotive industry into one of automation and self-reliance; data quality applications also enabled car makers in terms of distribution and promotions to improve their productivity. It has also enhanced their operation by helping to integrate technologies such as duty management and predictive maintenance. So let’s look into the impact of data quality on the automobile industry:
The Connected Car
Modern cars adopt new technologies such as Wi-Fi networking, onboard computing equipment, sensors, and specialized processors. Internet access provides drivers with autonomous driving experience and safety warning information, car health records, and fuel efficiency.
It is predicted that about 90% of new vehicles will have networking configurations in the coming years, which will increase the value of data quality analytics in automotive industries even more.
Supply Chain Advancements
Automotive manufacturers can use data quality to evaluate the cost, efficiency, and quality of product elements and machinery involved. It also evaluates information to estimate demand and aims to streamline the sourcing process to make it more cost-effective.
Data quality helps companies to study data relevant to the customer’s financial records and preferences. By integrating these details with the related demographics and environment, they can provide better financial strategies according to customer requirements.
Design and Production
Data associated with practical driving experience, including user preferences, maintenance information, and consumer segments, help automakers develop simple metrics such as safety, fuel economy, engine performance, and vehicle battery strength. Companies can implement optimization processes to increase their activities’ overall performance using the synergy of statistical analysis, data quality, and manufacturing models. As they make the design and development processes more aware, this has enhanced data quality applications’ value, helping to produce efficient transport systems.
Author: Kate S.
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