Enterprise Data Management

I am writing a paper about 5 terms that relate to the enterprise data management. These terms are UML, OLAP vs. OLTP, Data Warehouse, Data Mart and Multi-tier architecture. I found researching these terms gave me a better understanding about databases and how the information in a database is used in a business environment.

The first term, I'll be talking about is UML. UML is an acronym for Unified Modeling Language. UML is like an ERD. Per the web site http://intentsoft.com/technology/glossary.html "UML is an industry-standard language for specifying, visualizing, constructing, and documenting the artifacts of software systems standardized by the Object Management Group." Based on what I have read UML is used as a blueprint for software.

My next topic I will talk about OLAP vs. OLTP. OLAP stands for On-line Analytical Processing and OLTP stands for On-Line Transaction Processing. Just as the names stands for one is analytical the other is not. From my reading another different in OLAP is mission-critical production data and OLAP management-critical data accessed, I really not sure of what this actual means. I did fine some factual different between OLAP and OLTP, per web site http://www.cs.ualberta.ca/~zaiane/courses/cmput690/slides/Chapter2/sld021.htm OLAP data size is 100GB to TB, there can be hundreds of user, and number of records accessed are millions. OLTP data size is 100MB to GB, there can be thousand of users, and numbers of records accessed are tens.

The next topic is Data Warehouse. Simple put a Data Warehouse are several database collect demoralizes and logical assemble for easer use. Most of the reading on Data Warehouse was rather wordy and the explanation was lost to me. All of the articles I read about Data Warehouse talked about how it is used for business intelligence.

Data Marts are the next topic I will talk about. Data Mart is not places were you could buy cheap data (sorry for the bad joke I just had to be me). Data Marts are very similar to Data Warehouse, in that they both

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