An Analysis Of Key Enterprise Data Concepts

An Analysis of Key Enterprise Data Concepts

Garreth H. Dowlen II

Database Management Systems 405

Nasser Halwani

December 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:

* Data warehouse

* Data mart

* Data mining

* 3-tier architecture.

A datawarehouse 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. Datawarehouses exist to:

* make it easier, on a regular basis, to query and report data from multiple transaction processing systems

* 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 databases

* 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 datawarehouse 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. 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-hoc reports at a