Sept. 23 Required Readings: Database Technologies and Applications

1. Database

• Database management systems (DBM)- software apps that capture and analyze data and allows the definition, creation, querying, update, and administration of the database. It is also responsible for maintaing the integrity and security of the stored data and for recovering infer if the system fails.
• A database is created to operate large quantities of information by inputting, storing, retrieving and managing information.
• Database design and modeling: produce a conceptual data model that reflects the information to be put in the the database, many use the entity-relationship model to do this, and that will translate into a schema that implements the relevant information into a logical database design (the most popular is the relational model represented by SQL language- this model uses a methodical approach which is normalization.
• Databases can be classified by contents, application area, and by technical aspect.

     This reading was actually the most helpful and easy to understand out of all of the readings. I think it did the best job of explaining what normalization and a what a relationship model is. There were some parts that went over my head, but I think I picked up enough of the basics to understand the main concept of databases. I thought the History section was interesting and also hard to follow but I got the most out of the Design and Modeling section.

2. Entity Relationship Model in Database

• The ER model is a data model used for describing the data aspects of a business domain- it is a systematic way of describing and defining a business process with components linked by relationships.
• The database organizes and shows entities and the relationships that exist between them and that database.
• Entity- noun, capable of independent existence
• Relationship- verb, captures how entities are related to one another
• There are different levels of entity relationship models, these include: conceptual data model, logical data model, physical data model

     This reading was very dense and required the reader to have a lot of background information to understand some of the concepts. Even after reading the Database wiki site, I struggled to understand some of the terms and explanations. The author didn't give enough information for me to understand things like cardinality constraints and what a sound definition of attributes would be. I also believe one of the challenges was that I wasn't sure what in the article I needed to be understand more than the rest. I know it all pertains to class but I didn't know what I was supposed to understand at the end. Knowing that could've helped me weed through the very dense reading.

3. Database Normalization Process
     I think this article could have been much more helpful if it was in its original format. Trying to follow explanations that required images that were missing was very challenging. I could tell that a good deal of terms and definitions were trying to be explained to the reader in a simple way, but without the images I really gained nothing from the reading other than a definition of normalization and atomicity. But who know, it seems hard for me to grasp a lot of the tech concepts- so maybe even with the images I would have been just as lost.

• Normalization- natural way of perceiving relationships between data
• Atomicity- the indivisibility of an attribute into similar parts
• Primary key- the uniques identifier required of each row