Well, I don't know what yours are, but mine are:
1) Logically correct and complete.
2) Relational integrity
3) Data integrity
#1 means that the database design is correct and complete with regards to the atomization of data and the capture and maintenance of all pertinent information necessary to answer the problem at hand. No more, no less.
#2 means that the relationships between the tables are correct with regards to keys, foreign keys, and relational integrity (no orphans allowed) is enforced correctly.
#3 means that your fields are designed such that incorrect data can not be entered into a value, as much as possible. For example, setting field limits and data masks for special kinds of data to ensure that key stroke errors are caught and relayed back to the user before data is posted to the table. An example of this might be the pattern of a US social security number - we know there are nine digits in a social security number. The best way to ensure that the data is correctly entered is to force only NUMBERS for data entry, and add the "-" dashes progamattically. This way, there is no confusion about "do I enter the dashes or not?". Another data integrity feature is date valuation - only calendar dates may be entered. No Feb 30th, for example. In other words, you want to make your database design as "smart" as possible, to make sure that your data is correct at entry. Make it easy for the user to enter data, and make it hard, if not impossible, to enter bad data.
There are mainly three different Database architectures and they are network, hierarchical and Relational. The DBMSystems that follow the Relational architectural concepts are known as RDBMS. This is supposed to be superior in design and performance to the other two and there are, to my knowledge, no functional DBMS following the other two concepts in the market today.
There are three database models. The three database models are as follows : 1) relational 2) network data 3) hierarchical
Data integrity: Ensuring that data stored in the database is accurate and consistent by enforcing constraints, such as unique keys and foreign keys, to prevent invalid data. Scalability: Allowing the database to efficiently handle growing amounts of data and user load by optimizing data storage, indexing, and query performance. Maintainability: Simplifying the process of database maintenance, updates, and modifications by using normalization, clear data modeling, and documenting database structures.
Conceptual database design is the process of constructing a model based on the enterprise. Logical database design is the process of constructing a specific data model. Physical database design is the process of producing of the database on the secondary storage.
select, project, and join
High EfficientLow costHigh reliable
The mainly used databases are Microsoft SQL Server, Oracle, and MySQL. All three of these are relational databases and could easily handle databases containing millions of records.
What you really need is to set it up in a relational database. It is not a good idea to duplicate data or fields, as it can lead to problems. If you have a relational database then you can have each region in one table and the states in another and then set up relations between them. It can be complicated, but it is the better way to do it. Study up on relational databases and in particular many to many relationships as this what you particular scenario needs.
Hierarchical DBMSNetwork DBMSRelational DBMS
Sure thing, honey. Three common types of paper databases are address books, filing cabinets, and good old-fashioned Rolodexes. Just remember to keep those paper cuts at bay while you're flipping through those records!
Non-transitive dependency occurs in a database when a relationship between three or more attributes does not imply a direct relationship between all of them. Specifically, if attribute A is dependent on attribute B, and attribute B is dependent on attribute C, it does not necessarily mean that attribute A is dependent on attribute C. This type of dependency can complicate database normalization and design, as it can lead to redundancy and anomalies in data management. Understanding non-transitive dependencies is crucial for ensuring data integrity in relational databases.
what are the disadvantages of centralized database system