A database is formally defined as any collection of data, or information that is specially organized for rapid search and retrieval by a computer. To help explain how a database is created, I will be referencing firsthand experience in creating a Relational Database. For this example, I will be using a waterfall development model, where the creation follows a linear sequence to explain the process. There are 6 phases to follow when creating a database and are outlined in the database life cycle (DBLC). The stages of the Database Life Cycle are initial study, conceptual design, implementation and loading, testing and evaluation, operation, and maintenance and evolution. (Morris, Colonel, Rob, 2011)
When creating a database, I usually break down the initial study and conceptual design into another series of steps. The first of these steps is doing data analysis and gathering requirements. Data analysis can be conducted using any application you pick. Gathering requirements is done by interviews and then establishing business rules in which to follow. It’s these business rules that will establish the entities, attributes and relationships between entities that will make up your database.
This moves us to the conceptual design where normalization is used. Normalization is specially used to minimize data redundancies. There are many normal forms of normalizations that a business can choose to follow, however, most decided to stop at third normal form when creating their databases. An Entity Relationship Diagram (ERD) is then created to display your normalized database. An ERD should contain the relationships between entities, the relationship strength and contain notations on cardinality and connectivity. I choose to write my ERDs in Crow’s Foot Notation.
With a successful ERD, you are able to move into the implementation phase. I think of this as where the conceptual design is translated into a working physical design. It is here where you create a data dictionary to accompany your physical design. The actual physical design occurs on database management software application. For this example, we will be using Microsoft SQL Server. You will use SQL statements in this application to create tables, establish relationships, and insert information for the database you conceptually designed using the steps above.
When your actual database has been created and populated, you can use SQL Statements to query and test your database. For this step you will conduct end user testing. This essentially means that the people who will be using the database the most, will test whether it has the right functionality and if the database is easy to use.
Following end user testing, the database is now created and has been approved. You will be able to use the database to share information much easier with your peers. Note that maintenance and evolution occurs after the database has been created. It simply means that there will be a team that watches over the database and makes additions over time to improve its functionality.
Sharing Information Made Easier
As mentioned, the steps outlined above are the building blocks to making a database that can help share information easier. On a macro level, databases are broken down into a set of tables that consist of records and fields which may or may not have a relationship with other talks and records. On a micro level, each database has information broken down into records which is formally defined as a heterogenous collection of data . These records contain more than one field that help make this record unique and describe a particular attribute of this record. Sharing information is easier because of this micro organization. Users can use keys words, sort and filter options to retrieve or share the data that they want. These types of data retrievals are conducted by queries. An example of a popular query language is SQL. Query languages support database searching and operations by using commands such as “find,” “delete,” “print,” “sum,” and so forth. This language is what was being referenced above as “SQL Statements”.
Conclusion
In conclusion, databases are designed and maintained to ensure that data processing and information sharing is made easy. Following the right design and protocols can ensure functionality success and operational success. If a database is designed poorly, it will likely lead to monetary and operational issues in the future. As we move further into the information age, databases and best practices will be increasingly important. As well, many tools exist to help analyze the data that are stored in the databases. These BI tools allow companies to make actionable insights based on their stored data.