The highly competitive transportation

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In industry, speed and differentiation are key. From supply chains to mobility providers, organizations are scaling edge infrastructures to bring intelligence closer to vehicles. To cope with exponential data growth, enterprises are ramping up their cloud and data center infrastructures. Challenges like autonomous vehicles require incredibly large amounts of data and compute. Achieving these results requires agile, integrated, software-defined infrastructure, with specialized storage solutions to support workflows. The racing industry, for example, has expanded well beyond its previous capabilities. For example, data analytics at the edge and in the data center is used to design and upgrade over 150,000 parts for a racing car.

Another example is the transportation infrastructure of smart cities: smart roads and smart cars. Dell Technologies predicts that by 2025, the volume of data that will flow from 100 million smart cars worldwide will amount to 10 exabytes per month. To take advantage of the enormous opportunities in this data, we need to move from the current model of collecting, storing, and categorizing vehicle-generated data to a next-generation model that can collect, catalog, move, store, secure, and index nepal mobile database volumes of structured and unstructured data in real time from multiple sources, from mobile devices to the cloud and edge. A platform approach will help feed data into a network of partner solutions, enabling better analytics and increased visibility and transparency into the data. Only then can this data be used to manage and monetize connected and highly automated vehicles. If we continue to implement disparate systems, then compatibility issues and data fragmentation will prevent the expectations of autonomous and smart driving from being realized.

The manufacturing sector also relies on technology. Many state-owned companies have now been given large-scale tasks, and national projects have been defined for them, the successful implementation of which requires a major modernization of the current IT infrastructure of enterprises. This includes healthcare, education, housing and utilities, research organizations, and, of course, the digital economy. The national project to increase labor productivity, as well as a comprehensive plan to modernize and expand the main infrastructure, also require the collection, storage and analysis of data.