Cloud computing provides the benefit of having access to a reliable, scalable infrastructure without investing in hardware or configuration. Applications can take advantage of this capability by using it to dynamically add and remove servers as needed while still delivering near-linear scalability. This significantly improves the capacity of your application to handle load changes.

Companies can store data in three types of cloud environments: Public, Private, and Hybrid. It is ultimately up to your company's requirements as to which cloud solution is appropriate for it.

A bio-pharmaceutical giant capitalized on big data to solve complex issues - both product innovation and risk mitigation. With sensitive and complex clinical data, they needed a solution that would scale for hundreds of clinical data, so the pharmaceutical giant deployed a clinical data hub that ingested all kinds of data in a unique format. With this solution, they increased the number of studies and reduced time needed to refresh a study allowing researchers and doctors to manage more studies.

Big data technology was employed by a transportation and logistics service provider to efficiently give the finest carrier experience. Due to their inability to properly handle massive data, they dealt with severe barriers in their quest to construct the most efficient digital transportation network and offer the greatest carrier experience. They created an architectural structure that allows them to use Artificial Intelligence (AI) and Business Intelligence (BI) directly on their database's massive volumes of data while maintaining efficiency. This had a tremendous influence on business operations with their digital solutions, resulting in significant infrastructure savings and increased efficiency.

An automotive manufacturer used big data technology to derive value in its supply chain by preventing disruptions in supply and delays in production. Automotive manufacturing requires shipping of heavy parts and a complex supply chain, which can be a major logistical challenge. They used a multi-cloud data platform to integrate data from available sources, which led to a massive volume of data that was analyzed with analytic software to understand the entire logistical and supply chain system. The manufacturer was able to improve and drive efficiency to get parts to production plants without any delay.