Data are raw facts, means facts that have not yet been processed to reveal their meaning. (Rob Coronel 2008) Now a day, the main interest is database design and implementation for data storage and data management. The main reason for collecting, storing and managing data is to produce information that becomes the basis for rational decision making. For extracting necessary information from the data structures, Decision Support System (DSS) were developed. As the requirements increased, it was difficult for a DSS to extract all important and necessary information from the data structures. That is why, a new data storage system, called a database warehouse is developed. The purpose of this paper is to explain the basic concepts of Data Warehouses, advantages and disadvantages. Keywords: Decision Support Systems, Databases, Data Warehouse.
What is a Data Warehouse?3
Data Warehouse Vs Traditional Database3
Definition of Data Warehouse4
Types of data warehouses that can be built and managed by the organizations5
Enterprise data warehouses:5
Basic Process of Developing a Data warehouse:6
Extra Transform Load Process (ETL Process):7
Advantages and Disadvantages of Data Warehouses8
What is Business Intelligence?8
In this information age, management, executives and business users are using well organized data for decision support and the organizational planning. For decision making process, Decision Support Systems were developed. But due to the information requirement and their complexity, it was difficult for Decision Support System to extract all necessary information from the data. There for a new data storage system, called the data warehouse was developed. What is a Data Warehouse?
A data warehouse is a relational database. It is not used for daily route in transaction processing. It contains remarkable (having great significance) data derived from the transaction data. It also contains data from other sources like external systems, or applications. It is designed for query and analysis.
Data Warehouse Vs Traditional Database
As we know, a database is a collection of the relational data. A database and database software together we call the database system. A data warehouse is also a collection of relational data as well as supporting system. If we look closer to it, we will find that the traditional database and the data warehouse have indexes, fields, keys, views and etc. At this point, we noticed that there is no difference between the traditional database and the data warehouse. But there is a difference between them. The traditional database stores transactional data like relational, object oriented, network or hierarchical. While the data warehouses are mainly developed for retrieving historical transaction data for management, executives and business users for decision support and organizational planning. At this point you think that the data warehouse is just a big summarized database. Complete data warehouse architecture includes support for a decision support data store, a data extraction and integration filter, and a specialized presentation interface. (Rob Coronel 2008) In the data warehouse, the new generation tool called online analytical processing (OLAP), create an advanced data analysis environment that supports decision making, business modeling, and operational research. (Rob Coronel 2008) The OLAP systems share four main characteristics 1. They use multidimensional data analysis techniques
2. They provide advanced database support
3. They provide easy–to–use end–user interfaces
4. They support client/server architecture. (Rob Coronel 2008) Definition of Data Warehouse
Bill Inmon, the acknowledged “father” of...