Systems Analysis and Design Allen Dennis and Barbara Haley Text by ert554898

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									Data Storage Design
Chapter 11
Objectives
 Apply data base knowledge to select the
 appropriate data storage format
 consistent with user requirements.
DATA STORAGE FORMATS
Types of Data Storage Formats
 Files: electronic lists of data optimized to
 perform a particular transaction
 Database: a collection of groupings of
 information the relate to each other in some
 way.
 A Database Management System (DBMS) is
 software that creates and manipulates
 databases.
File Types
 Master files – store core, important
 information
 Look-up files – store static values
 Transaction files – store information that
 updates a master file
 Audit files – record before and after versions
 of data
 History (archive) files – store past information
Database Types
 Legacy database (you may come in contact
 with these)
   Hierarchical
   Network
 Relational database
 Object database
Relational Database Concepts
 Popular; easy for developers to use
 Primary and foreign keys used to identify
 and link tables
 Referential integrity ensures correct and
 valid table synchronization
 Structured Query Language (SQL)-
 standard language for accessing data
Object Database Concepts
 Built around objects consisting of both data
 and processes
 Objects are encapsulated (self-contained)
 Object classes – major object categories
 OODBMS – used primarily for applications
 with multimedia or complex data
 Hybrid OODBMS – both object and relational
 features
Comparison of Data Storage Formats
 Lets look at the table on page 365 to
 evaluate the criteria for selecting a data
 storage format
OPTIMIZING DATA STORAGE
Dimensions of Data Storage
Optimization
 Conflicting goals:
   Storage efficiency (minimizing storage space)
   Speed of access (minimizing time to retrieve
   desired information)
Storage Efficiency
 Minimize null values and redundancy
 Reduce update anomalies
 Normalization process optimizes the data
 storage design for storage efficiency
Optimizing Access Speed
 Techniques available to increase access
 speed after optimizing for efficiency
   Denormalization
   Clustering
     Intrafile
     Interfile
   Indexing
Denormalization
 Add redundancy back to data storage design to
 reduce the number of joins performed in a
 query
 Ideal for frequently queried but rarely updated
 data
   Look-up tables
   1:1 relationships
   Add parent attributes to child
   Star schema design data models
Clustering
 Reduce the number of times storage must be
 accessed by physically placing like records
 close together.
   Intrafile clustering – similar records in a table are
   stored together
   Interfile clustering – combine records from more
   that one table that are typically retrieved together
Indexing
 A minitable that contains values from one or
 more fields in a table and the location of the
 values within the table
 Similar to the index of a book.
Volumetrics – Estimating Data
Storage Size
 Raw data – sum of the average widths of all
 fields in a table.
 Calculate overhead requirements based on
 DBMS vendor recommendations
 Estimate initial number of records
 Estimate growth rate of records
Estimating Data Storage Size
 Field   Average Size (Characters)

 Order number                   8
 Date                           7
 Cust ID                        4      Initial Table Size        50,000
 Last name                      13     Initial Table Volume   3,185,000
 First name                     9
 State                          2      Growth/Month               1,000
 Amount                         4      Table volume @
 Tax rate                       2              3 years        5,478,200
 Record Size                    49
 Overhead (30%)                 14.7
 Total Record Size              63.7

								
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