In the contemporary business environment, the application of database and a data warehouse is essential for the normal functioning and development of business. At first glance, database and data warehouse may seem to be homogeneous and, therefore, replaceable by each other. However, in actuality, modern companies tend to develop both database and a data warehouse. The explanation of such a trend is quite simple since both database and a data warehouse are essential for the modern business and complement each other. In fact, database is mainly used to record current data, which is essential for any company, while a data warehouse is crucial for the effective analysis of data, which can be used for planning the further development of business. Hence, modern companies separate database and a data warehouse to record current information and keep information on current performance of a company, on the one hand, and to analyze data in depth with the help of a data warehouse, on the other hand.
In fact, in order to understand the necessity of such separation of database and data warehouse, it is important to understand the essence and function of both database and a data warehouse and principal differences between them. At the same time, it is important to lay emphasis on the fact that, without database and a data warehouse, modern companies cannot develop successfully because, today, information is a key factor that determines a successful marketing performance of companies and defines their future prospects. It proves beyond a doubt that functional differences are particularly important and they predetermine the co-existence of database and a data warehouse and prevent them from cohesion into a single database.
On analyzing differences between database and a data warehouse, it is worth mentioning the fact that database is designed to record data, which are stored in the form of tables, indexes, keys, views, etc. In contrast, a data warehouse is designed to respond and to analyze questions that are crucial for business (Behzad, 2003). In other words, a data warehouse provides not only the possibility to record and store data as an ordinary database does, but it is mainly designed for analysis of information stored. The latter is particularly important in the contemporary business environment, especially in a long-run perspective because routine recording of information, which is attributed to database, allows to keep the current performance of an organization balanced at the moment, but it is quite difficult to forecast any possible changes or develop new, more effective strategies without an effective analysis of data related to the performance of the organization (Andrew, 2003). Therefore, a data warehouse is needed to analyze data and respond to possible challenges the company can face in the future as well as it also allows developing mid- and long-term strategies on the basis of the analysis of the data stored and processed within a data warehouse.
Basically, the application databases are on-line transaction processing systems, where every transaction has to be recorded, and super-fast at that. For instance, a bank ATM has disbursed cash to a customer but was unable to record this event in the bank’s records. If this started happening frequently, the bank would likely to be ruined and ran bankrupt. Hence, the banking system is designed to make sure that every transaction gets recorded within the time customers stand before an ATM machine. This system is write-optimized.
On the other hand, a data warehouse is a database that is designed for facilitating querying and analysis. Often a data warehouse is designed as on-line analytical processing systems. These database contain read-only data that can be queried and analyzed far more efficiently compared to a regular on-line transaction processing application database. In this regard, a data warehouse is designed to be read-optimized. In fact, creation of a data warehouse leads to a direct increase in the quality of the analysis as the table structures, typical for databases, are simpler standardized and often denormalized to reduce linkages between tables and the corresponding complexity of queries. Hence, a data warehouse reduces drastically the cost-per-analysis and thus makes analysis faster and more efficient. Consequently, modern companies are interested in the development and co-existence of both database and data-warehouse. On the one hand, database are useful when current information and data need to be recorded and processed immediately, while, on the other hand, a data warehouse is particularly helpful when data need to be analyzed in details.
Thus, taking into account all above mentioned, it is possible to conclude that the application of both databases and a data warehouse are crucial in the contemporary business environment. At the same time, in spite of seeming similarities of databases and a data warehouse, modern companies do not create a single database since databases and a data warehouse basically perform different functions and their applications differ consistently. As a result, databases are designed to write records, while a data warehouse is designed to read records that determines the necessity of having both databases and data warehouse.

References:
Andrew S. (2003). Tanenbaum, Computer Networks (4th Ed), Prentice Hall.
Behzad, R. (2003). Principles of Data Conversion System Design. New York: Random House.
Rudin, W. (1976) Principles of Mathematical Analysis New York: McGraw-Hill.
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