An Analysis of Key Enterprise Data ConceptsGarreth H. Dowden II Database Management Systems 405 Nasser HalwaniDecember 14, 2004 An Analysis of Key Enterprise Data Concepts Business intelligence has several different meanings depending upon the organization and its goal. I general, it involves the collection of data and using it to predict future trends. This information is used to make decisions regarding the direction of said organization. Many businesses offer solutions that propose to pull together data from a variety of sources into a single repository and then analyze the data to gleam whatever information is needed. Regardless of the overall solution recommended, there are 4 basic concepts that they all employ: o Data warehouse o Data mar to Data minin go 3-tier architecture.
A data warehouse is a repository of transactional data that has been specifically structured for querying and reporting on the data contained within in it. The format of the data is not as important as is the fact that the data is to be stored for as long as needed. Data warehouses exist to: o make it easier, on a regular basis, to query and report data from multiple transaction processing systems o provide a repository of transaction processing system data that contains data from a longer span of time prevent persons who only need to query and report transaction processing system data from having any access whatsoever to transaction processing system database so use data models and / or server technologies that speed up querying and reporting and that are not appropriate for transaction processing. With data being captured from multiple operational systems, from different portions of the enterprise, the data warehouse becomes the only tool that can pull together this data to tell a single story. For example, the customer of a bank may use multiple delivery channels to interact with the institution and / or retrieve account information. The bank also collects information regarding the customer’s profitability to the bank, types of accounts opened, and tenure with the bank.
The Research paper on Data Warehousing Warehouse Operational Information
... is a Data Warehouse Data warehouse is the center of the architecture for information systems in the 1990 s. Data warehouse supports informational processing by providing ... perform well and must be available for transaction processing must carry the minimum amount of data if they are to have any ... Database. The next step was to decide what sort of query tool was to be used. After a complete evaluation ...
This information is collected by marketing, the call center, the website, host transaction systems, etc. To get a complete picture of customers and their habits, it is necessary to get all the information in a single location so that the appropriate queries can be developed. The end result is the telling of a story regarding customer behaviors. It is this business intelligence that enables management to make the appropriate and accurate strategic decisions.
Having a wealth of information at the enterprise level is definitely required but for the individual department within the organization, analysis of only a portion of the data may be needed; this is where data mart is most beneficial. A data mart is a database or collection of databases where the focus is on a particular topic or department. Staying with the banking analogy, the customer that uses the call center as a delivery channel is different than the customer that uses a retail banking office. Therefore, the call center will require a different snapshot of the customer than would another area of the bank. Being a more dynamic environment, the call center would likely have a need for ad-how reports at a moment’s notice. Using a data mart simplifies the process of getting to information in an efficient manner.
Retrieving the data is one thing; using that data to identify trends and patterns is quite another. This can be done manually but will often be time consuming and can yield less than accurate results. Data mining database applications are a proven technology that employs a form of artificial intelligence to identify trends and relationships amongst the data. Understanding the trends in the data is key to running an organization effectively. The most effective architecture to use the retrieve this data is the 3-tier architecture. It is considered more suitable for web based enterprise applications which are quickly becoming the standard.
The Business plan on Data Warehouse Information Database Analysis
... business-to-business and business-to-customer interactions. For examples, companies can make product information, design specification, white papers, and competitive data, order status information, ... benefit a broad range of data management applications. 5. Data Visualization Data visualisation makes it possible for ... season (input).Each node in the hidden layer is fully connected to the inputs which ...
Its effectiveness comes from the fact that an application is separated into 3 components: a presentation layer, a business logic layer, and a database layer. The presentation layer is how the information is delivered to the end-user. This is usually done in the form of a graphical user interface (GUI) that provides a streamlined presentation of the needed information. The business logic layer is where the business rules that drive the application reside.
It is also where requests are executed prior to being provided to the end-user. Finally, the database layer houses the information to be used by the application. The 3-tier architecture allows for changes to be made to either layer independent upon the others. This structure provides the ability for changes to either layer without impacting the other layers. This will allow the business to take advantage of and implement new technologies or make changes as needed. Customers now drive how they will interact with businesses today.
This being the case, businesses needs to have the business intelligence about its customers so that the proper strategic decisions can be made. The proper data warehouse or data marts and data mining tool will be the means by which this is accomplished. References Greenfield, Larry. (1995 – 2004).
Data warehousing. The Datawarehousig Information Center [Online]. web V. R. (1997).
An Introduction to Data Warehousing web.
