12.3: Physical DB Design Process
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- 93722
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\(\newcommand{\avec}{\mathbf a}\) \(\newcommand{\bvec}{\mathbf b}\) \(\newcommand{\cvec}{\mathbf c}\) \(\newcommand{\dvec}{\mathbf d}\) \(\newcommand{\dtil}{\widetilde{\mathbf d}}\) \(\newcommand{\evec}{\mathbf e}\) \(\newcommand{\fvec}{\mathbf f}\) \(\newcommand{\nvec}{\mathbf n}\) \(\newcommand{\pvec}{\mathbf p}\) \(\newcommand{\qvec}{\mathbf q}\) \(\newcommand{\svec}{\mathbf s}\) \(\newcommand{\tvec}{\mathbf t}\) \(\newcommand{\uvec}{\mathbf u}\) \(\newcommand{\vvec}{\mathbf v}\) \(\newcommand{\wvec}{\mathbf w}\) \(\newcommand{\xvec}{\mathbf x}\) \(\newcommand{\yvec}{\mathbf y}\) \(\newcommand{\zvec}{\mathbf z}\) \(\newcommand{\rvec}{\mathbf r}\) \(\newcommand{\mvec}{\mathbf m}\) \(\newcommand{\zerovec}{\mathbf 0}\) \(\newcommand{\onevec}{\mathbf 1}\) \(\newcommand{\real}{\mathbb R}\) \(\newcommand{\twovec}[2]{\left[\begin{array}{r}#1 \\ #2 \end{array}\right]}\) \(\newcommand{\ctwovec}[2]{\left[\begin{array}{c}#1 \\ #2 \end{array}\right]}\) \(\newcommand{\threevec}[3]{\left[\begin{array}{r}#1 \\ #2 \\ #3 \end{array}\right]}\) \(\newcommand{\cthreevec}[3]{\left[\begin{array}{c}#1 \\ #2 \\ #3 \end{array}\right]}\) \(\newcommand{\fourvec}[4]{\left[\begin{array}{r}#1 \\ #2 \\ #3 \\ #4 \end{array}\right]}\) \(\newcommand{\cfourvec}[4]{\left[\begin{array}{c}#1 \\ #2 \\ #3 \\ #4 \end{array}\right]}\) \(\newcommand{\fivevec}[5]{\left[\begin{array}{r}#1 \\ #2 \\ #3 \\ #4 \\ #5 \\ \end{array}\right]}\) \(\newcommand{\cfivevec}[5]{\left[\begin{array}{c}#1 \\ #2 \\ #3 \\ #4 \\ #5 \\ \end{array}\right]}\) \(\newcommand{\mattwo}[4]{\left[\begin{array}{rr}#1 \amp #2 \\ #3 \amp #4 \\ \end{array}\right]}\) \(\newcommand{\laspan}[1]{\text{Span}\{#1\}}\) \(\newcommand{\bcal}{\cal B}\) \(\newcommand{\ccal}{\cal C}\) \(\newcommand{\scal}{\cal S}\) \(\newcommand{\wcal}{\cal W}\) \(\newcommand{\ecal}{\cal E}\) \(\newcommand{\coords}[2]{\left\{#1\right\}_{#2}}\) \(\newcommand{\gray}[1]{\color{gray}{#1}}\) \(\newcommand{\lgray}[1]{\color{lightgray}{#1}}\) \(\newcommand{\rank}{\operatorname{rank}}\) \(\newcommand{\row}{\text{Row}}\) \(\newcommand{\col}{\text{Col}}\) \(\renewcommand{\row}{\text{Row}}\) \(\newcommand{\nul}{\text{Nul}}\) \(\newcommand{\var}{\text{Var}}\) \(\newcommand{\corr}{\text{corr}}\) \(\newcommand{\len}[1]{\left|#1\right|}\) \(\newcommand{\bbar}{\overline{\bvec}}\) \(\newcommand{\bhat}{\widehat{\bvec}}\) \(\newcommand{\bperp}{\bvec^\perp}\) \(\newcommand{\xhat}{\widehat{\xvec}}\) \(\newcommand{\vhat}{\widehat{\vvec}}\) \(\newcommand{\uhat}{\widehat{\uvec}}\) \(\newcommand{\what}{\widehat{\wvec}}\) \(\newcommand{\Sighat}{\widehat{\Sigma}}\) \(\newcommand{\lt}{<}\) \(\newcommand{\gt}{>}\) \(\newcommand{\amp}{&}\) \(\definecolor{fillinmathshade}{gray}{0.9}\)The design of a physical database is heavily influenced on integrity and performance for the system (Hoffer et al., 2015). To maximize efficiency for user interactions with an information system, minimizing time constraints associated with user interactions must be taken into account. According to Adrienne Watt, database design starts with a conceptual data model and produces a specification of a logical schema; this will determine the specific type of database system (network, relational, object-oriented) that is required. The relational representation is still independent of any specific DBMS; it is another conceptual data model (Watt, n.d.). The database design process is initialized from the logical data model that will be used in the database design and can be represented as an E-R (Entity-Relationship) diagram (Figure 1).
Physical database designs require preliminary pieces of information that are collected prior to development. For a physical file design and database design, normalized relations, attribute definition, descriptions of data handling, the expectations for response times, data security, backup, recovery, retention, and integrity of data, and descriptions of the technology are utilized to implement the database (Hoffer et al., 2015). Before commencing analysis and implementation of the database design, designers must first consult with customers to acquire relevant documents and data to be used in analysis and implementation to achieve the desired results based on the customers’ needs.
Physical database design is also concerned with the design of fields. A field is the smallest unit of application data recognized by system software. Fields are associated with the columns found in a relationship table and rely on the data types, coding techniques, data integrity, and handling of empty data entry. Efficient database performance relies on adequately defined fields and subsequently relies on adequate specifications for each field.
The format for data storage is an imperative decision to be made when considering storage space and data-related integrity as shown in Figure 1. This format can be integrated with the selection of data types that are only needed for the database design to be implemented. Data types can be categorized as a string, numerical, and datetime data values, and can be further decomposed into varying lengths of data for their respective categories as shown in Figure \(\PageIndex{2}\).
String |
Numeric |
Date/Time |
---|---|---|
CHAR |
SMALLINT |
DATE |
VARCHAR |
INTEGER |
TIME |
CLOB |
DOUBLE |
TIMESTAMP |
Coding and compression techniques are critical for handling data storage within fields. Allowing for smaller-sized codes reduces the space usage of data values within databases. An example of such a coding technique could involve cross-referencing to other tables in order to retrieve a field value. Aside from using data types as a form of data integrity, other forms of data integrity to be considered in a physical database design include default values, which are automatically assigned unless specified otherwise by a user; range control, which a preset range limit specifies the set of values a field can be assigned; and null control, which restricts null values.