A logical data warehouse is a data management architecture for analytics, which combines the strengths of traditional repository warehouses with alternative data management and access strategy. It provides an abstraction and integration layer that hides details from users of the data, thus allowing the users to easily access data in traditional data warehouses. With the growth of data volume, data will be multi-structured and won’t fit into the existing databases, thus leading to the formation of many data stores which won’t allow getting full value out of the data. Whereas, the logical data warehouse allows one to access and govern these different data stores as if they were a single logical data store, thus making it easy. Read more at: http://www.datavirtualizationblog.com/logical-data-warehouses-matter/

One of the common business challenges is that the required information by business users is not provided fast enough. The most commonly used company’s data structure is an Enterprise Data Warehouse (EDW), where when information is required, a data mart is created in a separate database, this process is problematic due to the cost of maintaining multiple databases and also the integrity and consistency of the information stored is questionable. However, the delay between the time that the information is required and when it is provided is the real problem. So, the following changes must be made in order to succeed. An information system that transforms data into relevant information very quickly should be provided and all databases should be centralized from the same point. Also, real-time information should be provided and the time to market with short and agile projects should be improved. And finally, new sources of information of different types should be incorporated. Thus, the companies should consider the logical data warehouse approach. Read more at: http://www.datavirtualizationblog.com/enterprise-data-warehouse-no-longer-suffice-data-driven-world/