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Understanding Database Concepts: Terminology, Architecture, and Technology

Explore database terminology, structure, and technology including field, record key, sort keys, redundancy, DBMS architecture, and data languages. Learn about fixed vs variable length records, sort keys, and database components.

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Understanding Database Concepts: Terminology, Architecture, and Technology

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  1. Chapter 12File Processing and Data Management Concepts

  2. Presentation Outline • Terminology • Database Technology • The Architecture of a Database Management System (DBMS) • The Database Administrator

  3. I. Terminology • Field • Data Occurrences • Fixed vs. Variable Length Records • Record Key • Sort Keys

  4. A. Field A field is the smallest block of data that will be stored and retrieved in the information system. Other names for field include data item, attribute, or element. Field 1 Field 2

  5. B. Data Occurrences A specific set of data values for a record in a file. 1 2 3 4 5 The above table contains 5 occurrences of account records for the general ledger account file.

  6. Fixed Length Records Both the number of fields and the length of each field are fixed. Strength: Easier to manipulate records. Weakness: Must accommodate maximum sizes. Variable Length Records Both the number of fields and the length of each field are variable. (See Fig. 15-1 on p. 603) Strength: Less waste of memory when maximum sizes do not have to be accomodated. Weakness: Record manipulation is more difficult. C. Fixed vs. Variable Length Records

  7. D. Record Key 1110 A record key is a field or combination of fields that uniquely identifies a particular record in a file. 1500 2105 2110

  8. E. Sort Keys • Primary sort key – The first field used to sort the data occurrences in a record set. • Secondary sort key – A field used to determine relative position among a set of data occurrences in a record set. • Tertiary sort key – Additional fields beyond primary and secondary sort keys that are required to uniquely identify data occurrences in a record set.

  9. II. Database Technology • The Problem of Redundancy • The Components of a Database

  10. A. The Problem of Redundancy That is not what we show per our records. • Redundancy occurs when different areas of an organization use the information system to store the same information in more than one place. • Results in update anomaly.

  11. B. The Components of a Database Management System • Data Description Language (DDL) • Data Manipulation Language (DML) • Data Query Language (DQL)

  12. 1. Data Description Language (DDL) Defines the logical structure of the database (known as the schema). Defines the following: • Name of data fields. • Type of data (numeric, alphabetic, etc.) • Number of positions (length of field). • May also define subschema (i.e., individual user views)

  13. 2. Data Manipulation Language (DML) Pull a trial balance. • The DML consists of the commands for updating, editing, manipulating, and extracting data. • Structured query language (SQL) is a common DML in relational settings. Structure Query Language (SQL)

  14. 3. Data Query Language Query by Example (QBE) A data query language is a user friendly language or interface that allows the user to request information by simply filling in blanks. Represents a special type of DML.

  15. III. The Architecture of a Database Management System (DBMS) • The Database Architecture • The Conceptual Architecture and Entity-Relationship (ER) Diagrams • Logical Data Structures • The Physical Structure

  16. A. The Database Architecture Database contents Uses of database Desired reports Information to be viewed Conceptual Level Logical data structures: Tree Network Relational Logical Level Access Methods: Sequential Access Indexed Files Physical Level

  17. B. The Conceptual Architecture and Entity-Relationship (ER) Diagrams PART_NO NAME • Square boxes are used for entities (separate tables). • Ellipses are used for attributes (table columns). • Diamond shaped boxes depict relationships. COST PART STORED AT LOCATION WHSE ADDRESS

  18. C. Logical Data Structures • Tree or Hierarchical Structure • Network Structures • Relational Structure • Selection • Projection • Join

  19. 1. Tree or Hierarchical Structure • A parent record can have many children. However a child record can have only one parent. • Can only model 1:1 (one-to-one) and 1:* (one-to-many) relationships. • Commonly used with accounting data. Can only access data by going from a parent to child. Balance Sheet Assets Liabilities Equity Current Assets Current Liabilities Revenues Long-term Assets Long-term Liabilities Expenses

  20. 2. Network Structure • Eliminates the distinction of parent and child records. A parent can have many children and a child can have many parents. • Can model 1:1 (one-to-one), 1:* (one-to-many), and *:* (many-to-many) relationships. • Must know the physical structure of the data in order to access it.

  21. 3. Relational Structure • Relational databases organize and store data in two dimensional tables consisting of rows and columns. • Relationships among tables are represented by common data values in different tables. • Straight forward in terms of organizing and searching the data. • Possesses ad hoc search capabilities.

  22. 3a. Selection Savings Table Produces a horizontal subset (includes entire row) of a relation which satisfies a boolean predicate. (Savings) Balance < 5.00

  23. 3b. Projection Savings Table Constructs a vertical subset of a relation. The subset is obtained by selecting specified attributes and removing others. (Savings) Name Balance < 5.00

  24. 3c. Join Table R Table S A join is used to combine 2 tables. The attribute used to join must be in both tables. R |X| S

  25. D. The Physical Structure • Sequential Access • Indexed Files

  26. 1. Sequential Access • Records can only be accessed in a predefined sequence. For example, if there are 100 records in a file, one must access the first 99 records before accessing the last record. • Generally useful for batch processing when nearly all records must be accessed.

  27. 2. Indexed Files • Any attribute can be extracted from the records in a primary file and used to build a new file whose purpose is to provide an index to the original file. • First, the index is searched to find a specified value of an attribute such as an customer account number. • Second, the disk addresses are used to directly retrieve the desired records • See Fig. 12-13 on p. 427.

  28. IV. The Database Administrator This is not quite what we need. The database administrator is a person who coordinates data management activities such as approving the physical contents and user views of the database.

  29. Summary • Fields and keys • Three Components of a DBMS • Three Types of Database Architecture • The Database Administrator

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