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How do you explain the relational database design process?
The design process consists of the following steps:
- Determine the purpose of your database.
- Find and organize the information required.
- Divide the information into tables.
- Turn information items into columns.
- Specify primary keys.
- Set up the table relationships.
- Refine your design.
- Apply the normalization rules.
What is the implication of having a poorly designed database for an organization?
A poorly designed database may provide erroneous information, may be difficult to use, or may even fail to work properly. Most of these problems are the result of two bad design features called: redundant data and anomalies. Redundant data is unnecessary reoccurring data (repeating groups of data).
What is considered bad data?
Simply put, bad data refers to data that is inaccurate for a business. Bad data could include data that is missing key elements, data that is not relevant for the purposes it is to be used for, data that is duplicated, data that is poorly compiled and so on.
Is it bad to ignore the rules of database design?
Ignoring these goals will lead to designs that are flawed in their basics, although structurally and mathematically correct. Designing a database is not a deterministic task; two database designers may follow all the rules and normalization principles for a given problem, and in most cases they will generate different data layouts.
What happens if there are no constraints in database design?
If no constraints or very few constraints are implemented from the design stage, the data integrity will have to rely entirely on the business logic, making it susceptible to human error.
Why do Database designers need to make special considerations?
Special considerations must be made by the designers in order to keep the efficiency and usability of the database, if data volumes are to be big.
What are the common practices of database design?
You are faced normally with confusing tables, views, columns, values, stored procedures, functions, constraints, and triggers that take a long time to make sense to you. And, once they do, you start noticing many ways to improve and take advantage of the stored information.