The need for a robust data warehouse has become evident after analytic requirements were at odds with the existing operational database performance. To run a complex query on the database requires it to enter a temporary state which is unsustainable for transactional databases, gives rise to the need for a data warehouse.
Today, the most critical asset for the enterprise to remain in the competition is Data Warehouse. As promised, 2019 has become the most prominent year of the cloud-based data warehouse. With Azure SQL Data Warehouse, Microsoft again brought revolution in the market.
Microsoft has established Azure SQL Data Warehouse as a viable alternative to on-premises data warehouses. It is considered as a complete package of price and performance. By providing 10x faster computing on the TPC-H benchmark, it is still a cost-effective solution for enterprises.
Azure SQL Data Warehouse is a distributed, enterprise-class database that can process large amounts of relational and non-relational data. It can grow, deploy, and pause in seconds. Being a part of Azure services, Azure SQL DW can handle software patching, backups, and maintenance, automatically. It uses Microsoft’s MPP (massively parallel processing) architecture that was initially designed to operate large on-premises data warehouses for enterprises.
Companies, irrespective of their sizes, are moving to the cloud to operate their data warehouses. They are looking for a data warehouse that can work with the existing data tools, integrate with their multiple data sources, and utilize their existing skills. Azure SQL DW enables companies to use their own traditional business intelligence skills for building a robust data warehouse in Azure.
In this Industry Perspective, we’ll talk about how Microsoft’s Azure SQL DW is generating value for enterprises. We will also highlight various aspects related to Data Warehouses such as how it will benefit enterprises and how they are continuously improving their application performance without increasing their budget.
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