Businesses around the world are faced with many challenges when attempting to compete and gain a competitive advantage over their competition. The members of the management team within these businesses need to make quick and accurate decisions which will often impact the company and all of its employees, possibly for years to come. One of the worst situations for one of these decision makers to find themselves in is when they know that all of the information they need is available; but they are unable to retrieve that information in an accurate and useful way. In no field is this truer than in the manufacturing industry, where one bad decision could cost the company millions of dollars, especially in regards to the contract proposals and bidding process. One tool which can aid in this decision making process when the required information is spread out across the company, is called data warehousing.
A Data Warehouse is a separate database that is specifically designed for aiding the decision making process. This new database can carry out this function by being subject-oriented, integrated, time-variant, and non-updateable. (Menninger, 1994) These four concepts are vitally important for a data warehouse to supply the decision making information that it is tasked to provide. In the example of the manufacturing company bidding or quoting on a contract, the Subjects would be Customers, Suppliers, Employees, and Parts. All the information found in the Data Warehouse would be oriented around these key subjects. The data, as mentioned earlier, would also be collected from many different sources and integrated together to form one set of valid information. The third element that would be important, centers on the element of t...
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Menninger, Dave. "And now, introducing the data warehouse...." Data Based Advisor Nov. 1994: 126+. Computer Database. Web. 30 Nov. 2011.
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Rosen, Cal. "'Schema wars' miss warehousing basics." Computing Canada 20 Apr. 1998: 34. Computer Database. Web. 30 Nov. 2011.
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http://go.galegroup.com.portal.lib.fit.edu/ps/i.do?id=GALE%7CA20502639&v=2.1&u=melb26933&it=r&p=CDB&sw=w
White, Colin. "Why a data warehouse? A recent survey shows how some companies handle informational processing." Database Programming & Design Sept. 1993: 27+. Computer Database. Web. 30 Nov. 2011.
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Traditional business intelligence tools are being replaced by data discovery software. The data discovery software has numerous capabilities that are dominating purchase requirements for larger distribution. A challenge remaining is the ability to meet the dual demands of enterprise IT and business users.
As defined by Kroenke Database is an integrated, self-describing collection of related data. Data is stored in a uniform way, typically all in one place- for example, a single physical computer. A database maintains a description of the data it contains and the data has some relationship to other data in the databa...
On the output side of the data warehouse, there must be interfaces that allow a user to ask for data from the devices (PCs or terminals) that he typically use. The information in the warehouse must be structured, so that users can easily obtain answers to their questions.
A data warehouse can be implemented through two-tier or three-tier architectures depending on the business requirements (Database Modeling & Design, 1998).
Laudon, K., & Laudon, J. (2007). Essentials of Business Information Systems (7th ed.) (Bob Horan, Ed.). Upper Saddle River, New Jersey: Pearson Prentice Hall.
The information can be made into categories which can be outputted to make choices for the future of the company. Information will be kept in the database and the database will contain tools to help process the information in multiple ways.
Ans: Data warehouse can be defined as the repository of data. It is a pool of data which helps in decision making. It contains historical data as well as current data. The data usually first structured in a form that can be easily read by analytical processing activities like OLAP, data mining etc. The benefits of data warehouse are: it helps in decision making; it provides the single version of truth though the data is collected from various sources which in turn will help to determine the current state of business and identify problems, enhanced system performance and accessing of data is very simple. As many applications are web based, even the users access data via web and the data from web can be put into the data warehouse; web accessibility is important with data warehouse.
Data warehousing is a difficult system and has to have the capability deliver quality data. An operational database is one which is used by organizations to run its day to day database activities. They are designed to handle rapid transaction processes with systematically updates. Velocity is important to operational databases. They are most commonly operated by office staff, and are on the order of megabytes of data to gigabytes. Database consistency checks and constraints are rigidly enforced. They contain the latest technology necessary to operate organizational functions.
What is a data warehouse and what are its benefits? Why is Web accessibility important with a data warehouse?
The Revolution in Database Architecture, by Jim Gray, describes the path that Gray thought that the evolution of the Database Architecture would take after 2004. He considers that databases had been stagnated for several years and that, beginning in 2004, the development of several technologies would pave the way into a revolution in the database world.
In today's fast paced world, data warehouse plays an important role in all sectors including financial, IT, retail and many more. Over the past decade data warehouse has been used to derive business solutions and increase productivity for potential success. After analysing various success factors to define a good solution the main factors noted and discussed in this review are those involving the system process, information quality and organisational impacts. Success of a warehouse architect depends on many organizational factors which include data warehouse, ETL, data modelling, security and business intelligence. By taking into account all these factors
[7] Elmasri & Navathe. Fundamentals of database systems, 4th edition. Addison-Wesley, Redwood City, CA. 2004.
The last decade can be marked as a period of significant changes in the business world. Being accustomed to utilize computers as a powerful tool with its office applications such as Microsoft Word and Excel. In the 1990s office workers first faced the opportunity to share information using the Internet (McNurlin, 2009). However, the situation became even more different with the transition to the third millennium. With a further development of information technologies, the majority of big enterprises had to reconstitute their business processes and to make the transition to the Internet economy. Enterprise resource planning (ERP), supply-chain management (SCM), customer relationship management (CRM) software and the variety of other information systems became essential components of the new economy. It can be expected, that all these complex solutions were designed to bring great benefits for different sides of the corporate activity, in particular, decisions made by top-managers are expected to become nearer to the ideal, customer service is to be improved and collaboration more prolific. Nevertheless, to ensure the desired results it should be taken into account that the key concept of these reorganizations is an information or a data, dealing with which can be a serious issue, and wide utilizing of the data warehouses in contemporary organizations confirms this fact.
A data warehouse comprised of disparate data sources enables the “single version of truth” through shared data repositories and standards and also provides access to the data that will expand frequency and depth of data analysis. Due to these reasons, data warehouse is the foundation for business intelligence.
Prior to the start of the Information Age in the late 20th century, businesses had to collect data from non-automated sources. Businesses then lacked the computing resources necessary to properly analyze the data, and as a result, companies often made business d...