5/4/2023 0 Comments Bigquery vs redshiftUnlike on-premises data warehouses, pharma majors do not have to invest on hardware related to number of nodes and disks. They also function without interfacing with the hardware, with a service layer that allows IT teams to manage things remotely via the cloud.Ĭompared to on-premises data repositories, cloud-based data warehouses allow data managers to plan, procure, maintain data securely and efficiently. In terms of functionality, cloud data warehouses have a completely different approach to loading data, querying and moving the data around the various levels in the company. Cloud-based data warehouses do not need physical hardware and its quicker to set up. One of the key differences between traditional databases and cloud-based databases is that the latter is designed keeping elasticity and scalability in mind. The global Data Warehouse as a Service (DWaaS) market size is expected to grow at a Compound Annual Growth Rate (CAGR) of 22.3% to reach USD 12.9 billion by 2026 from USD 4.7 billion in 2021. As pharma companies brace with the reality of being more data-driven to get better insights and achieve top-of-the-line revenues, cloud data warehouse technologies are the answer for faster insights. But with a big data boom, access to huge amounts of historical and current information via traditional data warehouses became a formidable task.īiotech companies need to retrieve information for analysis, interpretation, trend identification regardless of whether objectives focus on clinical trials, regulatory compliance, marketing and sales alongside distribution. Historically, data management systems and warehouses were based on heavily structured paradigms that assumed the data was being captured for specific questions. ![]() The use of big data in drug research stemmed from more efficient data access and more secure data repositories for biopharma companies.
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